Every session topic, grouped by category. No timings, no speaker bios — just the substance.
Hello Future, Meet Reality is a fast, frank panel discussion with leaders on what actually held up when AI hit real-world conditions: legacy systems, security teams, governance, data mess, change fatigue... the lot. No magic wand, just real decisions, real trade-offs, and get their real view of what ""future-ready"" looks like in an enterprise.
The Visibility Gap: Turning Observability into DevSecOps Signals (sponsored by Datadog)Security teams and dev teams share the same production environment but operate from different signals. Without runtime context, security monitoring has blind spots with misconfigured infrastructure and threats in flight. This session draws on Fone Dynamics' ISO 27001 journey to show how runtime telemetry, cloud audit logs, and code scanning give DevSecOps and SecOps teams shared context.
AI innovation depends on consistent, trusted data. When disrupted, AI systems and the business decisions they support are at risk. In this session, learn how cloudnative protection models support AI pipelines, reduce recovery time after disruptions, and minimise operational overhead. Discover best practices to protect AI and cloudnative applications in AWS while innovating with confidence.
This session demonstrates how quickly and easily enterprise-grade AI security can be applied to your Amazon Bedrock projects. See the new Prisma AIRS AI-security platform in action on AWS: We explore Model Scanning and AI Posture Management; then dive into Runtime Security; and finally examine automated AI Red Teaming and AI Agent Security. Unlock your AI-led innovation - securely.
Generative AI systems evolve constantly, and the impact of prompt or model changes often isnt clear until real users interact with them in production. In this session, learn how teams using Amazon Bedrock safely experiment with AI at runtime, testing models and prompts with targeted rollouts, evaluating system outputs online, and optimising against real business result
This joint discussion explores how organizations are moving from simplistic operational AI to agentic AI that drives innovation and new revenue. Through industry use cases and platform strategies, it shows how AI-enabled systems are disrupting markets and reshaping competitive advantage, with practical guidance for growth.
Software development has fundamentally changed in 2026, driven by vibe coding, AI agents, and RAG/MCP. APIs are the interface layer for AI systems to perform meaningful work. For this to succeed, your APIs must be discoverable, consistent, and usable by both developers and agents. Postman is now central to designing, managing, and iterating on your APIs to be sustainable in this new era.
Geopolitical instability, rising CX demands, rapid tech shifts, and escalating cyber threats converge faster than manual processes can handle. Join our expert panel as they leverage AWS and AI to build customer solutions, elevate engagement, and neutralise cyber threats. We'll share real deployments, proven governance, and measurable gains in efficiency, resilience, and customer impact.
As one of Australia's leading general insurers, Auto & General knew AI would play an important part in their future IT operations. To ensure success, the team embarked on a comprehensive observability maturity journey to build solid foundations, governance, and structure. Learn how A&G worked with New Relic to successfully lay observability foundations for the AI age.
For the National Australia Bank (NAB), operating across multiple cloud environments and delivery platforms is a necessity but results in a critical challenge - fragmented visibility and the costly reality of "design once, build thrice" security controls. Learn how NAB moved beyond compliance to empower every engineering team with a unified view of risk, achieving security at speed and scale.
Postman and the Future of AI-Driven API Development in 2026 (sponsored by Postman, Inc)Software development has fundamentally changed in 2026, driven by vibe coding, AI agents, and RAG/MCP. APIs are the interface layer for AI systems to perform meaningful work. For this to succeed, your APIs must be discoverable, consistent, and usable by both developers and agents. Postman is now central to designing, managing, and iterating on your APIs to be sustainable in this new era.
Today's leaders face pressure to prove AI ROI, yet many struggle to realise value on fragmented foundations. Miro on AWS solves this by uniting teams, tools, and collaborative AI workflows in one workspace — amplifying the way teams actually work with enterprise scale and security. In this fireside chat with Culture Amp, hear how turning AI ambition into real outcomes works in practice.
Need flexibility across cloud and on-premises This session reveals how delivering cloud anywhere gives you the architectural freedom to run data and AI across AWS, clouds and hybrid environments. Discover how a unified data fabric simplifies governance and security, accelerating AI-driven innovation. Achieve unified control and compliance for highly regulated environments.
Organisations today depend on fast, secure access to data to support mission-critical operations and evolving AI workloads. With Oracle AI Database services available on AWS, your team can streamline data integration and deliver high-impact solutions for semantic search, fraud detection, quality control, and much more.
Your Agents Should Be Durable (sponsored by Temporal)Building AI agents is easy — making them production-ready is hard. Crashes, API failures, and state management are just a few challenges when moving from PoC to production. Learn how durable execution with Temporal makes it simple to build reliable agents that run for days, weeks, or months, using a code-first approach developers love.
Learn how GitLab Duo Agent Platform (DAP) powered by Amazon Bedrock brings agentic AI into every stage of the software development lifecycle while keeping data, logs, and inference traffic inside your AWS environment. We'll show how teams can orchestrate AI-assisted workflows for planning, coding, security, and compliance using Amazon Bedrock foundation models behind GitLab's AI Gateway.
Transform enterprise automation with Boomi's AI agent ecosystem. Learn to use Agent Designer to visually build agents that connect across systems, and Agent Control Tower for centralised governance, compliance, and performance monitoring. Securely orchestrate your AI lifecycle at scale with Amazon Bedrock.
In an era where AI accelerates software development, organisations must address supply chain risks. Using insights from Chainguard's research and observed industry patterns, we walk through the mechanics of these compromises without the hype. Attendees will leave with straightforward approaches for enhancing software integrity and building long-term trust in their development pipeline on AWS.
As AI moves from assistants to agents, success depends on contextwhat the system attends to and acts on. In this lightning talk, well show three examples of context-aware agents in the enterprise through quick demos: meeting coordination, engineering issue resolution, and sales forecasting, highlighting how the right context enables reliable execution at work.
Technology leaders need operations that evolve from reactive to autonomous. Enable teams to resolve incidents faster with intelligent systems that handle routine issues automatically. Shift from reactive responses to prevention, tool sprawl to coordination, manual work to automation. See how an AWS-powered platform learns from every incident to deflect toil, protect revenue, and scale.
A forward-looking view of how enterprises are transforming customer experience through unified, AI-driven architecture. By moving away from fragmented solutions to an integrated platform spanning AI-powered engagement, automation, and orchestration, organisations can deliver more consistent, scalable, and outcome-focused experiences in an AI-first era.
Most teams have "done DevOps" but still face low platform adoption, rising cloud costs, lagging security, and fragile incident response. This session explores the "After" state: treating your platform as a product, with golden paths, built-in security, AI-driven simplicity, and reliability by defaultusing Harness as the model for a governed, cost-aware, AI-native developer experience.
Human risk is a critical layer of any security strategy. Human risk management addresses how employee behaviorfrom accidental sharing to shadow AI usecreates organizational exposure. Discover how Mimecast, on AWS, helps identify risky behavior, protect critical data and account access, and support compliance. Real-world insights. Behavioural analytics. Adaptive controls. Measurable ROI.
How fast can AI drive results Banks seek competitive advantage while staying compliant, and the public sector aims to enhance citizen services and boost productivity. In this session, we demonstrate how Synthetic Data and robust AI Governance operationalise AI with confidence. Learn how SAS Viya on AWS enables effective deployment, unlocking faster, better decisions through a proven AI framework.
Managing EKS clusters means correlating logs, metrics, IAM policies, and network configurations under pressure. The AWS DevOps Agent, announced at re:Invent 2025, changes this workflow fundamentally. In this session, you'll watch a live demonstration where the DevOps Agent autonomously investigates an EKS service failuretracing issues from Pod logs through VPC Security Groups without manual intervention. You'll learn how the agent correlates cross-service dependencies, generates verified remediation plans, and integrates into existing SRE workflows.
Modern IoT platforms are inherently data platforms. Events flow through APIs, queues, AWS Lambda Serverless functions, storage systems, and device networks before becoming meaningful data. When something goes wrong, tracing a single event across these distributed components quickly becomes painfuland the question shifts from _what happened_ to _where do I even start looking Ill walk through three practical observability patterns drawn from building and operating a production, event-driven IoT healthcare platform on AWS that processes tens of thousands of device events daily. Using OpenTelemetry, AWS X-Ray and Honeycomb, well explore techniques for gaining visibility into asynchronous event pipelines, correlating activity across services, and tracing events as they move through distributed systems. Youll leave with three concrete patterns you can apply immediately to your own event-driven data systems.
Explore a practical framework to think about and build secure AI agents on Amazon Bedrock AgentCore. This session covers threat modeling specific to agentic workloads, including how agents interact with tools, memory, and external systems, and what you need to watch out for. You'll learn how to apply AWS security best practices across AgentCore services, and walk away with actionable patterns. Suitable for developers and architects building AI agents who want to move from prototype to production with confidence.
Moving an AI agent from prototype to production requires more than optimism. This session tackles the "Day 2" engineering challenges of scaling resilient agentic architectures on AWS. Learn practical patterns for handling traffic spikes, optimizing throughput, and controlling costs using Amazon Bedrock models and AgentCore Runtime. We'll cover tool filtering strategies, when multi-agent architectures make sense, how to apply evaluations effectively, and how to harden your APIs against real-world load. Leave with concrete techniques to transform brittle GenAI prototypes into production-grade systems that survive viral launches and demanding enterprise workloads.
AI Native Development: Strategies and Impact across Amazon and AWSAmazon and AWS have evolved beyond AI-assisted development to embrace AI Native practices, integrating AI as a partner throughout the software development lifecycle. Learn how their teams leverage AWS foundational tools including Kiro, and Amazon Bedrock. Discover effective Prompt Driven Development methodologies and grassroots adoption strategies from early champions. See how Amazon enables teams to provide AI with right context through strategic use of MCP, RAG and custom models trained on Amazon technical knowledge. Understand the culture transformation required across multi-thousand person organizations, where every role must evolve. Gain actionable insights to accelerate your AI Native journey.
Automation has long relied on orchestration: predefined workflows, rigid control flows, and human-managed exceptions. That model breaks down as systems become adaptive, distributed, and autonomous. In this session, we explore the shift from orchestration to intent-based supervision, where humans define purpose, constraints, and authority, while agents decide how to act within those bounds. Drawing on real-world agentic architectures, the talk shows how dynamic discovery, semantic negotiation, and closed-loop feedback replace static workflows. Attendees will learn how to design automation that scales safely, remains governable, and adapts as context changes, without removing human judgment from the system.
Evolution of Automation: Orchestration to Intent-Based SupervisionAutomation has long relied on orchestration: predefined workflows, rigid control flows, and human-managed exceptions. That model breaks down as systems become adaptive, distributed, and autonomous. In this session, we explore the shift from orchestration to intent-based supervision, where humans define purpose, constraints, and authority, while agents decide how to act within those bounds. Drawing on real-world agentic architectures, the talk shows how dynamic discovery, semantic negotiation, and closed-loop feedback replace static workflows. Attendees will learn how to design automation that scales safely, remains governable, and adapts as context changes, without removing human judgment from the system.
Explore practical applications of Agentic AI through two real-world case studies. First, dive into a Hong Kong weather agent built with Amazon Nova Act, featuring conversation flow design and meteorological data integration. Watch a live demo showcasing natural language interaction for weather information retrieval and trend analysis. Next, discover a mathematics teaching AI agent developed using the Strands Agents framework, demonstrating personalized math video creation through automatic content generation. Both cases include comprehensive code demonstrations, providing developers with concrete references for AI agent application development on AWS.
Amazon and AWS have evolved beyond AI-assisted development to embrace AI Native practices, integrating AI as a partner throughout the software development lifecycle. Learn how their teams leverage AWS foundational tools including Kiro, and Amazon Bedrock. Discover effective Prompt Driven Development methodologies and grassroots adoption strategies from early champions. See how Amazon enables teams to provide AI with right context through strategic use of MCP, RAG and custom models trained on Amazon technical knowledge. Understand the culture transformation required across multi-thousand person organizations, where every role must evolve. Gain actionable insights to accelerate your AI Native journey.
When a Strands Agent fails across five Lambda log streams with no correlation, debugging takes 20 minutes minimum. This session demonstrates a structured observability layer that reduces diagnosis to under two minutes. You'll learn how Lambda Powertools Tracer wraps Strands tool invocations as X-Ray subsegments, how Powertools Logger injects AgentCore session correlation IDs across invocations, and how Powertools Metrics surfaces tool retry frequency as CloudWatch alarms — before timeouts occur. The session covers three production failure classes — tool timeout, reasoning loop, and retry storm — and delivers a reusable CDK construct providing full instrumentation for any Strands Agent Lambda deployment.
Scaling AI successfully isnt just about moving fast — its about building the right foundations first. In this session, learn how Flybuys focused early on AI governance, steering documents, and engineering standards to enable smooth, secure AI adoption at scale. Well explore how upfront investment in guardrails, training, and approval processes allowed teams to deploy AI capabilities faster and with confidence. Youll hear how Flybuys is embedding governance and security expectations into engineering workflows using Kiro, including standardised steering patterns, approval pathways, and controlled rollout of AI capabilities such as Powers. Attendees will gain practical insights into how slowing down early can unlock faster, safer AI delivery across the organisation.
As organizations scale AI agent development, robust enterprise architecture patterns become essential. In this advanced session, we'll explore how Amazon Bedrock AgentCore enables teams to build modular systems using their preferred frameworks while sharing tools through MCP gateways. Learn about A2A collaboration, shared memory, identity-based access controls, and integrated observability. Discover practical strategies for secure runtime deployment, standardized tool integration, evaluation frameworks, and end-to-end monitoring. Leave with actionable insights to build secure, scalable agent infrastructures that balance centralized governance with team autonomy.
Explore how to build production-grade AI agents with persistent, context-aware memory using Amazon Bedrock AgentCore. This expert session covers architectural patterns for implementing four memory typesepisodic, semantic, preference, and summaryenabling agents that recall past interactions, recognize cross-session patterns, and maintain conversation context. You'll examine real implementation techniques for long-term memory management, workflow orchestration, and retrieval strategies using Amazon Bedrock. Leave with practical skills to design intelligent agents that deliver faster, more accurate responses in high-stakes applications. Ideal for architects and engineers ready to move beyond stateless AI toward genuinely intelligent, memory-enabled systems.
AI coding agents introduce failure modes traditional CI/CD pipelines weren't built to catch — deleted tests, weakened type constraints, silent cross-service regressions. This session examines practical pipeline-level guardrails for agentic workflows running on ECS Fargate and distributed CI environments. You'll learn which failure patterns agents introduce that humans rarely do, which automated checks reliably catch them, and how to structure pipelines that apply appropriate scrutiny to agent-generated code without blocking developer velocity. Leave with concrete, implementable patterns covering test integrity enforcement, type safety validation, and cross-service regression detection — applicable whether you're managing one agent or coordinating many across multiple repositories.
What does it mean to be a serverless developer in the era of GenAI What disciplines do you need to master to build cloud-native, serverless solutions today In this session, we'll walk through a day in the life of a serverless developer and explore the core principles, architecture patterns, frameworks, and how to leverage GenAI tools to build your next-generation serverless application.
Modern AWS environments generate more alerts than teams can realistically investigate. This session demonstrates a proof-of-concept that transforms Slack alerts into automated investigation workflows using AI.Learn how to trigger parallel queries across CloudWatch, Amazon EKS, Prometheus, and deployment history when an alert fires — returning correlated summaries with probable causes and dashboard links directly in Slack.You'll leave understanding practical integration patterns for AI-assisted triage, telemetry hygiene requirements, and guardrails for safely introducing AI into production incident response. Discover how AI augments — rather than replaces — your existing observability stack, meaningfully reducing time-to-insight during incidents.
Real engineering happens in legacy codebases, not blank canvases. This session explores deploying multi-agent AI workflows using Kiro against brownfield production systems with tangled dependencies and accumulated technical debt. Learn how to orchestrate specialised agents for system mapping, dependency navigation, code generation, and validation within complex existing architectures. We'll examine practical strategies for providing sufficient context to agents, implementing guardrails to prevent regressions, and coordinating multiple agents toward shared goals. Walk away with actionable techniques for applying agentic AI to real-world codebases, understanding where automation delivers value and where human judgment remains irreplaceable.
In this lightning talk, we'll walk through a real-world architectural pattern used in production: combining AWS CloudFront with Route 53 latency-based routing to make your ECS-backed services truly global. Starting with the problem of slow response times for APAC users, we'll build up a practical active-active architecture step by step. You'll see how CloudFront sits in front of your regional ALBs, how WAF is woven into the design from the start rather than bolted on later, and why getting your domain configuration right — distinguishing between your ALB origin domain and your public-facing CloudFront alternate domain — is critical to making this pattern work correctly.
Architecture diagrams show what you built. They don't explain why. At Bell Financial Group, every major technology choice — from landing zone design to compute platform to database engine — is captured in an Architecture Decision Document that forces honest evaluation of trade-offs. In this talk, the Head of Engineering at Bell Financial Group walks through the real decisions behind their AWS platform: why ECS Fargate beat EKS, when DynamoDB wins over relational databases, why the entire infrastructure is written in TypeScript CDK, and the deliberate constraints they place on Lambda usage. No slides full of boxes and arrows — just the reasoning, the trade-offs, and the lessons learned building a regulated financial services platform on AWS.
Cloud infrastructure changes carry hidden risks that manual reviews often miss. This session demonstrates how to build a pre-deployment blast-radius reviewer using Amazon Bedrock that analyzes infrastructure-as-code diffs, IAM policy changes, and deployment metadata to produce structured risk assessments in seconds. Attendees will learn how to design grounded AI workflows that identify affected services, security gaps, cost implications, and rollback considerations, and how to apply Bedrock guardrails for consistent, safe outputs. The session includes a live demonstration and covers practical patterns for integrating AI-generated assessments into existing engineering approval and governance processes without sacrificing speed or reliability.
You cant turn your head sideways without seeing a slew of articles, blogs, or videos about AI, and most of them focus on developer tooling and writing code. But AI isnt just for developers. Its an incredibly powerful tool for operations folks, too.In this lightning talk, Ill share how I use Kiro CLI and the Kiro console with AWS Model Context Protocol (MCP) integrations for day-to-day cloud operations. From information gathering and log analysis to reporting and IAM policy interpretation, these tools help reduce cognitive load and speed up your output when working with AWS environments.Ill also discuss how I used Kiros spec-driven development approach to build a Python-based reporting tool, despite not being a software developer.This session is designed to make AI tooling feel approachable and practical for anyone working in AWS — not just developers.
Parsing LLM responses as JSON worksuntil truncation, missing fields, or malformed output breaks your pipeline. This session examines Amazon Bedrock Structured Output, which enforces schema compliance at the model level rather than relying on prompt instructions. You'll learn how to define response contracts using JSON Schema, understand where native structured output differs from prompt-based approaches, and see practical patterns for integrating reliable model responses into production systems. Attendees will leave with concrete techniques for eliminating output validation failures, designing more resilient AI workflows, and understanding the architectural implications of treating model responses as typed, validated data rather than freeform text.
With AWS ap-southeast-6 (Auckland) now open, New Zealand organizations can repatriate workloads from Sydney. This advanced session provides practical migration strategies minimizing downtime and eliminating data loss across every layer of your stack. You'll learn region-to-region migration patterns for: *Storage*: S3 replication, EBS snapshots, EFS cross-region transfers *Databases*: RDS read replicas, DynamoDB global tables, self-managed EC2 database replication *Applications*: Lambda, ECS/EKS workload migration, EC2 AMI copying Walk away with a prioritized migration playbook, realistic RTO/RPO targets, and battle-tested sequencing strategies for large-scale data transfers without extended application outages.
Managing infrastructure as code sounds straightforward until you're wrangling hundreds of modules across multiple teams and accounts. In this session, a Platform Engineer and Lead Architect share hard-won lessons from building and scaling IaC platforms at large organisations — covering module composition strategies, state isolation patterns, and CI/CD pipelines that keep deployments safe and reproducible. You'll walk away with practical design patterns you can apply immediately, whether you're laying the foundations of your first landing zone or untangling a sprawling estate that's grown faster than its architecture.
Gain deep visibility into the performance and reliability of autonomous agents with Amazon CloudWatch. This session showcases how CloudWatch delivers endtoend observability for agentic AI workloadstracking decision quality, token efficiency, and workflow execution at scale. Explore prebuilt dashboards and advanced metrics that help you optimize agent performance, control operational costs, and maintain consistent behavior across complex intelligent systems. Walk away ready to implement productiongrade observability that ensures your AI agents operate reliably, make optimal decisions, and deliver measurable outcomes at scale.
Discover the future of software development as we explore the transformative power of agents with Kiros spec-driven development in modernizing your entire software development lifecycle (SDLC). Agentic AI is impacting software development by automating tasks, improving efficiency, and enabling more autonomous workflows throughout the development lifecycle. It allows teams to go beyond simple code generation to handle project planning, designing, testing, documentation, building agents into workflows, and retiring technical debt. Join us to explore how these powerful capabilities work together to help organizations accelerate from prototype to production ready applications.
AWS Game Day : Secret Agent UnicornsAWS GameDay is a gamified learning event that challenges participants to use AWS solutions to solve real-world technical problems in a risk-free setting. As a new hire at Unicorn.Rentals, the worlds largest mythical creature rental company, youll test your AWS knowledge in an interactive, team-based, risk-free environment! The Secret Agentic Unicorns GameDay covers the different components of AgentCore, guiding participants through agent creating using Strands, A2A, and other AgentCore technologies. Youll get real world experience creating and learning about AgentCore agents, and have fun along the way.
Embark on a faster, smoother cloud transformation with agentic AI and integrated solutions. This session reveals how AWS Transform accelerates your cloud journey, addressing migration and modernization challenges through intelligent automation. Through real-world examples, discover how to leverage this powerful integration to fast-track your cloud adoption and transformation efforts. With the specialized AI agents of AWS Transform, customers can migrate VMware workloads to Amazon EC2, modernize .NET applications to cross-platform .NET, and modernize IBM z/OS mainframe applications, delivering transformation projects up to 4x faster.
Explore the intersection of AI and FinOps in this advanced session. First, discover how Kiro CLI can simplify AWS cost management by analyzing trends, explaining spend, and recommending optimizations like rightsizing and Savings Plans. Then, dive into FinOps for AI- learn how to track and control generative AI costs across Amazon EC2, Amazon SageMaker, Amazon Bedrock, and more. We'll share architecture patterns, cost-saving strategies, and real-world examples to help you build scalable, production-ready AI solutions while staying on budget. Whether you're optimizing existing workloads or launching new AI initiatives, you'll leave with practical tools to maximize value.
AWS Game Day : Secret Agent UnicornsAWS GameDay is a gamified learning event that challenges participants to use AWS solutions to solve real-world technical problems in a risk-free setting. As a new hire at Unicorn.Rentals, the worlds largest mythical creature rental company, youll test your AWS knowledge in an interactive, team-based, risk-free environment! The Secret Agentic Unicorns GameDay covers the different components of AgentCore, guiding participants through agent creating using Strands, A2A, and other AgentCore technologies. Youll get real world experience creating and learning about AgentCore agents, and have fun along the way.
Discover the latest features of Amazon Quick Suite, a generative AI-powered business intelligence platform transforming organizational data workflows. Explore the newest capabilities including Quick Sight for interactive visualizations, Quick Flows for workflow creation, Quick Automate for intelligent automation, and Quick Research for comprehensive analysis. Learn how custom chat agents, knowledge spaces, and workplace extensions integrate seamlessly to enhance productivity through natural language interactions across your organization.
Many teams move fast with agentic AI prototypes that impress in demos but stall in productionblocked by gaps in reliability, accuracy, and safety. In this session, AWS agentic AI technical leaders will help builders rethink how to build and scale production-grade, trustworthy agentic AI. Learn proven patterns to build and deploy agents that earn trust in the real world. See AWS agentic AI platform Amazon Bedrock AgentCore in action. Discover how AWS customers move fast from sparks of experiment to scaled AI-driven innovation with trust at the core, transforming industries.
Prepare for the AWS Certified AI Practitioner exam with this study session. Review questions from the official practice question set. Ask questions of the subject matter expert leading the study session. Continue preparing for your exam with confidence following the four-step plan on AWS Skill Builder.
This session demonstrates how Kiro brings discipline and clarity to AI-assisted software development, ensuring generated code aligns with intended functionality and architecture. Explore Kiro's innovative spec-driven development approach for AI coding. Learn how to leverage structured specifications as a single source of truth, contrasting with unstructured 'vibe coding'. Discover how Kiro uses AI to generate detailed requirements, design, and task documents, guiding AI agents in code creation. Experience a workflow that enhances collaboration, maintainability, and documentation accuracy.
For modern consumer brands, winning means moving at the speed of culture. Zuru uses Amazon Bedrock and Twelve Labs to analyze up to 10,000 TikTok videos a day, rapidly identifying viral trends, emotional cues, and content patterns to create creator briefs in hours instead of weeks. Join this session to see how AWS gives Zuru a measurable edge, from 30 million organic views in seven days to 50x faster content creation, with industry peers now looking to replicate its speed-to-market advantage.
Every month, Transurban handles 5.5 million customer interactions across its Linkt brand — and is reimagining every one of them. Built on Amazon Connect, Transurban's AI-powered customer service platform has evolved from simple chatbots to multi-turn conversational AI and personalised experiences that are already lifting bot containment and freeing agents for higher-value work. Join this session to hear how Transurban is aligning people, process, and AI to transform customer service, what's coming next with Amazon Connect Cases and Email, and the hard-won lessons from scaling AI in a complex enterprise.
Join us for an engaging session on AI Agents and Tools in AWS, where well explore how to build intelligent, autonomous systems using Amazon Bedrock and open-source frameworks. Learn about function calling, ReAct patterns, and AWSs comprehensive agent platforms. Well dive into practical demonstrations using Strands and CrewAI, and discover how to leverage protocols like MCP and A2A for seamless tool integration and agent collaboration. Perfect for developers looking to create production-ready AI solutions.
Discover how Stockland, one of Australia's largest diversified property groups, built an intelligent AI assistant on AWS that puts enterprise knowledge at everyone's fingertips. This session explores a multi-agent system powered by Amazon Bedrock & Strands SDK and embedded in Microsoft Teams, that enables teams to streamline vendor management, automate routine tasks and accelerate decision-making. Learn how Stockland built intelligent workflows that transform procurement data into actionable insights, reducing manual effort while improving accuracy and compliance.
Discover how Amazon leaders across Zoox, Prime Video, and Amazon Stores are leveraging AI to power their next-generation innovations with AWS and create better experiences for customers. Through three key stories discover how customer needs sparked transformative experiences: fan feedback revolutionising sports broadcasting with AI-powered highlights, shopping patterns evolving Amazons mobile commerce platform, and robotics and automation delivering advances in supply chain optimisation and fulfillment. Learn the best practices Amazon has applied using AWS that can help scale innovation in your organisation.
Prepare for the AWS Certified Solutions Architect — Associate exam with this interactive study session. Review the AWS Certified Solutions Architect — Associate Official Practice Question Set, and get your questions answered by the subject matter expert leading the study session.
As Worley's software landscape expands, manual license governance struggles to keep pace with scale and complexity. While manual optimisation has delivered measurable results, a sustainable approach is needed to scale these outcomes. Software Intelligence Advisor (SIA) is Worley's agentic AI solution that enables optimal license decisions and empowers end users. Underpinned by AWS native data platforms, SIA combines deep usage intelligence with a conversational agent that meets users within existing collaboration tools. Through trusted, context-aware conversations, the agent validates usage patterns and encourages better behaviours — delivering scalable, human-centred optimisation and a pragmatic path to learning what agentic AI can deliver.
When Lendi Group launched Project Aurora on AWS, they bet big on a single super-agent with 270 tools. It floppedtechnically impressive but commercially useless. The agent couldn't sell. The breakthrough came from treating AI like a workforce: specialist agents with clear roles, sales logic embedded in the funnel, and relentless measurement. Engagement tripled. This talk shares the hard lessons from Lendi's 16-week sprint: why capability isn't outcome, why your best prompt engineer might be a 23-year-old closer, and how to architect agentic systems that actually convert.
Discover how Flybuys achieved rapid contact centre transformation through early Amazon Connect adoption using AI-powered capabilities and a disciplined Test, Learn, Iterate approach. Starting with a focused pilot, they deployed AI-driven features like intelligent routing, real-time sentiment analysis, and automated quality assurance. They progressed through Launch, Activate, and Consume phasescapturing baseline metrics, scaling through peer-led training, and continuously refining AI performance based on weekly feedback loops. The results: reduced AHT, improved CSAT, 100% AI-powered QA coverage, and measurable ROI. This demonstrates that early AI adoption delivers calculated, data-driven transformation.
In one of Australia's most operationally complex industries, Team Global Express (TGE) turned data into a strategic asset, and AI into a competitive edge. In 2025, TGE invested in data modernisation, establishing an AWS native data platform which now serves as the operational heartbeat of its logistics network. On this foundation, TGE is delivering compounding business value through rapid deployment of AI solutions across multiple domains. Join this session to learn how TGE secured board-level backing, built a lean AI team, and is scaling pragmatic, cost-effective AI — including the lessons learned along the way and whats next on their roadmap.
Discover how Sportsbet, Australia's leading sports betting platform, transformed its technology organization through strategic AWS partnerships. Learn how they built an enterprise-wide AI learning culture that achieved record-breaking certification results, and completed a serverless-first modernization that delivered significant cost savings and emissions reductions while handling massive scale. This session shares practical strategies for building executive buy-in, establishing effective AWS partnerships, and creating a culture where innovation thrivesdemonstrating how to focus internal resources on competitive differentiation while partnering for technical expertise to accelerate transformation.
Most organisations use AI to help developers code faster, but few have figured out what needs to change when building is no longer the bottleneck. This session introduces AI-DLC, the next evolution in how teams deliver software: a methodology that compresses specification timelines from months to weeks, and fundamentally changes how product teams operate. SEEK's Principal Product Manager shares how AI-DLC reshaped their people, process, and technology, and how they're now scaling across multiple product teams. You'll hear what's working, what's hard, what they're still figuring out and what it means for how your organisation delivers.
Many teams move fast with agentic AI prototypes that impress in demos but stall in productionblocked by gaps in reliability, accuracy, and safety. In this session, AWS agentic AI technical leaders will help builders rethink how to build and scale production-grade, trustworthy agentic AI. Learn proven patterns to build and deploy agents that earn trust in the real world. See AWS agentic AI platform Amazon Bedrock AgentCore in action. Discover how AWS customers move fast from sparks of experiment to scaled AI-driven innovation with trust at the core, transforming industries.
Discover how to build powerful AI agents using Amazon Bedrock's suite of tools, with a focus on Amazon Bedrock AgentCore. This session explores how Parrot Analytics leveraged the modular components of Amazon Bedrock AgentCore and Amazon Nova foundational models to achieve 10x the processing speed of manual classification across 2M+ entities. We will dive into prompt and context engineering, knowledge bases, and observability for production agentic workloads.
What if your engineering team could deliver a production-ready feature in two days that would traditionally take one month When Xero partnered with AWS, that's exactly what happened. In this session, we'll take you inside a real-world AI-Driven Development Life Cycle (AIDLC) workshop run against a live production use case. Working across an existing brownfield codebase, the Xero engineering team reached MVP in just two days against a feature that would have taken a month using traditional development methodology. We'll unpack what made that possible, what we learned along the way, and how those lessons are now shaping a plan to scale the AIDLC methodology across the entire engineering organisation.
From initial idea to executionlearn about Canva's journey migrating MySQL workloads from Amazon RDS to Aurora at scale. Discover how Canva achieved meaningful performance improvements, cost savings, and operational efficiencies through this strategic migration. This lightning talk shares real-world insights on planning and executing large-scale database migrations, key Aurora best practices for optimizing cost and performance, and how the latest monitoring features help maintain efficiency as you scale. Learn how AWS Countdown Premium (CDP) accelerated and de-risked Canva's migration, delivering tangible business value while minimizing operational disruption.
Discover how SafetyCulture, the global workplace operations platform used by 70,000+ organizations, achieved a 90% reduction in daily data pipeline execution time while processing the same data volumes on Amazon Redshift. Join this session with SafetyCulture data engineering team to learn how their team transformed a complex, slow-running data warehouse into a high-performance, AI-ready analytics platform using modern lakehouse architecture principles.
Learn how Roller Software grew from an Australian startup into a global venue management platform serving 3,000 venues across 30 countries and delivering 120 million experiences annually. Using AWS multi-tenant architecture, Roller maintains 99.99% uptime while processing $4 billion in transactions each year through their modern monolith application. This session covers practical strategies for tenant isolation, infrastructure scaling, and enterprise-grade security. Youll discover how to leverage AWSs native multi-tenant capabilities and get a proven roadmap for scaling your SaaS business from startup to enterprise while keeping costs efficient and operations excellent.
AWS Graviton-based Amazon EC2 instances provide the best price performance for workloads in Amazon EC2. In this session, dive deep into the AWS Graviton processor and learn about its workload performance, energy efficiency, and software offerings. Hear from Atlassian as they share their Graviton adoption journey and practical tips for migration success. Learn about common use cases, best practices to optimize your workloads across various applications, customer success stories and how you can accelerate your AWS Graviton journey.
AI agents are powerful but riskythey can access sensitive data, trigger workflows, and make autonomous decisions. Kasada and AWS are helping enterprises adopt agents with confidence through comprehensive AI agent trust management that protects legitimate AI agents while detecting and blocking malicious automated visits. Kasada's platform, integrated with AWS services, enables organizations to distinguish trusted agent traffic from sophisticated bot threats, monitor for anomalous behavior, and maintain agent integrity against evolving AI-powered attacks. Join Kasada and AWS experts to explore a practical framework for managing agent trust: how AI and agentic traffic are being abused today, where risks appear across discovery and checkout, how teams decide when to allow or block agents, what new protocols like Web Bot Auth do and where they fall short, and what Kasada has built for agent traffic visibilityall while maintaining seamless customer experience.
Squiz, a global Digital Experience Platform provider, is transforming how organizations deliver conversational search experiences. By adopting Amazon S3 Vectors, Squiz reimagined its ingestion pipeline — increasing data processing speed by 50% and shifting from bespoke, always-on infrastructure to a scalable serverless model. This allows Squiz to seamlessly scale from 25,000 to millions of vectors per client, while significantly reducing costs. Hear how this shift freed engineering teams to focus on RAG innovation rather than infrastructure management, and how it powers smart video search capabilities across their platform.
AI coding agents are transforming how developers build and operate modern cloud-native applications. With tools such as Kiro CLI, Kiro IDE, or any MCP-compatible AI coding assistant, developers are embracing AI to move faster and scale smarter. This session explores how MCP servers help developers streamline code generation, deployment, and debugging by embedding infrastructure awareness directly into the AI assistant. Learn how Xero is leveraging MCP to speed up development, simplify operations, and deliver more reliable containerized apps at scale. Xero will also share their success story using Kiro CLI, Prometheus MCP, EKS MCP, and AWS Knowledge Base MCP to identify and resolve Prometheus cost spikesslashing costs by 40%.
As business demands evolve, architectural patterns must evolve too. SafetyCulture and Buildkite implemented cell-based architectures driven by distinct business objectivesscaling for hypergrowth and enhancing infrastructure resilience. SafetyCulture's expansion plans required proactive architectural evolution to unlock unlimited scaling capacity. Buildkite needed to meet stringent security isolation requirements while achieving scale through repeatable deployment units. This session shares real-world experiences as both companies designed and implemented cell-based architectures for their SaaS platforms. Discover how SafetyCulture identified bottlenecks, redesigned systems for isolation and resilience, and aligned technical capabilities with business growth targets. Learn how Buildkite leveraged cell-based design to achieve both scale and security isolation. Walk away with actionable patterns for building resilient, scalable architectures.
Businesses capture millions of conversations daily, sales calls, support interactions and compliance discussions, yet most of this intelligence remains locked away. Standard dashboards and predefined reports cannot address every customer's unique questions. Dubber, a world leader in conversation capture and intelligence, built Insight Agent on AWS, enabling users to ask bespoke, natural language questions across conversations and structured data to receive context-aware answers in seconds. Learn how Dubber innovated from static dashboards to surfacing business value moments, and now to agentic AI that compresses time to value, making conversation intelligence accessible, scalable and viable.
Australian fintech leader BGL demonstrates their systematic approach to scaling agentic AI. Starting with Claude Code on Amazon Bedrock for developer productivity, BGL built OpsGorilla, a Slack-integrated agent serving 200+ employees. BGL extended AI agents to customer-facing innovation. BGL's Roni AI autonomously drafts annual compliance work for Self-Managed Superannuation Funds, reducing accountants' workload from days to hours. Built on Claude Agent SDK and Amazon Bedrock AgentCore, BGL's implementation showcases practical architectural patterns for organizations scaling AI agents from developer tools through enterprise operations to customer solutions.
We're past the hype phase and into the "figuring it out" phase. AI is reshaping how we build, hire, and collaborate, but the reality on the ground doesn't always match the pitch. In this session, Pushpay shares what they are actually seeing across teams and organizations: the common traps, the unexpected side effects, and the coping strategies that are actually working. Come ready for an honest, practical conversation about thriving with AI rather than just surviving it.
How Affinda leverages Amazon Bedrock (Claude), SageMaker, EKS & CloudFormation to deliver intelligent document processing at enterprise scale, cutting setup time and costs by 90% with 95%+ accuracy. This session will demonstrate how Affinda powers real-world AI product development from Affinda's Intelligfent Document Processing platform to Pathfindr's (acquired by Affinda) custom AI agents. The session will showcase the complete journey of building Honey Insurance's voice agent - Australia's first voice agent in financial services, and how the Affinda-AWS partnership enables rapid AI product development for Enterprises.
Dive into AWS networking fundamentals. Learn essential skills configuring your network in a single region before scaling to global, multi-Region architectures. In this session, explore various VPC connectivity methods, hybrid network integration, and secure traffic management techniques. Whether new to AWS or wanting to expand networking building blocks, this session delivers practical insights into best practices and proven architecture patterns for establishing global connectivity.
MedAdvisor, Australia's leading medication management platform connecting over 90% of community pharmacies, faced a critical challenge: pharmacists were losing hours daily to manual documentation, diverting time from patient care. To solve this, MedAdvisor built an AI-powered Scribe using Amazon Nova on Amazon Bedrock. The tool listens to pharmacy consultations in real time, transcribes conversations, and automatically generates structured clinical notes. Through iterative prompt engineering, output quality improved from 3.5 to nearly 4.5 out of 5, surpassing market alternatives. Now in beta across Australia, the solution went from concept to production-grade clinical documentation in under six months.
Software companies developing AI solutions face unique monetization challenges. AI compute costs run 3-5x higher than standard applications, per-user pricing often yields negative margins, and profit margins typically fall 10-30 points below traditional SaaS. This session introduces a proven framework to help you navigate AI pricing complexities. Learn how to identify value capture attributes, select appropriate pricing models, and build sustainable monetization strategies. We'll cover when to begin pricing considerations, how to apply an AI monetization framework to your solutions, and how to develop an approach tailored to your company's position. Whether defining your initial AI pricing strategy or validating your current approach, gain actionable insights to maximize the value of your AI investments.
Discover how hipages, ANZ's leading online construction marketplace, redefined their software development lifecycle by embedding Claude Code on Amazon Bedrock into daily engineering workflows. Join this session to get practical insights into maximizing Claude Code on Bedrock, understanding the decision process behind selecting this solution, and learning how hipages is pioneering an AI-first strategy that's transforming operations across their entire business.
Most AI agents fail not because of models, but because they cant access trusted external data. This session shows how InfoTrack used Model Context Protocol (MCP) to connect agents to authoritative data sources via a compliant and secured gateway.
Protecht, a global leader in enterprise risk management software, partnered with AWS and Caylent to build Cognita AI, an embedded AI assistant purpose-built for governance, risk, and compliance (GRC). Backed by a $280M PSG investment, Protecht built Cognita on a production-grade Amazon EKS foundation, integrating Amazon Bedrock and Anthropic's Claude models with a RAG architecture grounded in Protecht's proprietary GRC content. The result is a contextual, explainable, and auditable AI assistant that guides risk professionals through complex workflows, earning high accolades at the Gartner Enterprise Risk, Audit & Compliance Conference and setting a new benchmark for investor-grade, regulator-trusted AI in months.
his session explores how Canva leverages Karpenter to scale and optimize diverse workloads on Amazon EKS. Learn how Canva manages AI workloads using On-Demand Capacity Reservations (ODCRs) and EC2 Capacity Blocks for ML, while maximizing resource utilization by intelligently co-locating CPU and GPU workloads on GPU nodes. We will dive into NodePool management strategies for efficient scheduling of AI workloads and examine how Canva uses a range of Amazon EC2 instance types to operate a multi-tenant container orchestration platform for all workloads, optimizing for cost-effectiveness and resource efficiency. Ideal for platform engineers and Kubernetes operators looking to optimize their EKS clusters for both AI and general workloads at scale.
When you're building multi-tenant vector search but can't control what customers throw at you, every indexing decision — isolation, embedding, chunking, partitioning — becomes a bet you're making blind, and this talk gives you the framework to make the right ones.
Sonder's mission is to empower people to be at their best, delivering the right care at the right time to over 1 million members globally across employers, universities, and insurance partners. To scale this mission without compromising quality, Sonder built an AI Copilot entirely on AWS, a 100% human-in-the-loop system designed with safety-first approach where Care Specialists remain at the centre of every interaction, with reinforcement learning from human feedback (RLHF) continuously improving the Copilot's performance. This session explores the architecture behind it, including real-time triage, knowledge retrieval, and escalation workflows and shares the tangible business impact: faster response times, greater operational efficiency, and new service and revenue opportunities unlocked by AI.
Hnry, a fast-growing fintech startup, faced a critical challenge: their lean engineering team lacked capacity for thorough security reviews and penetration testing. Traditional solutions like hiring security specialists or engaging consulting firms would compromise their velocity and budget. By adopting AWS Security Agent, Hnry gained enterprise-grade security capabilities without enterprise overhead. The AI-powered tool integrated into their development workflow, providing real-time security feedback, automated design reviews, and on-demand penetration testing. This enabled Hnry to maintain startup speed while achieving robust security posture, proving small teams can deliver enterprise-level security through intelligent automation.
Most teams are still piloting AI - TeamForm is shipping it. In this session, we show how we built enterprise and production-ready generative dashboards in weeks on AWS Bedrock and AgentCore, and how an AI-native operating model made that velocity possible. Learn what it actually takes to operationalise AI across product and engineering, not just prototype it.
AI agents are no longer just answering questions - they're booking flights, managing infrastructure, and calling APIs on our behalf. But when an agent acts autonomously, who's really knocking on the door This talk explores how Kinde is rethinking authentication and authorisation for a world where your users aren't always human, covering machine-to-machine identity, delegated scopes, and why traditional auth flows break down when agents enter the chat.
LegalScout helps Australian SME law firms turn Generative AI into a competitive advantage by securely leveraging their own client data and confidential matters to work smarter, not harder. Built with Australian lawyers on AWS using Amazon Bedrock for inference and Amazon S3Vectors for secure document searches, it automates repetitive work, streamlines workflows, and improves drafting, contract review, and research to boost productivity, reduce costs, and lift accuracy while maintaining strict privacy and compliance.
What happens when live video meets AI and the scalability of AWS This session explores how Unleash live harnesses AWS to deliver real-time vision analytics, moving from ingestion to insight in milliseconds. We detail the architecture of cloud-native pipelines that process live streams at scale and apply custom computer vision models across the energy, security, and infrastructure sectors. By combining edge connectivity with AWSs elastic infrastructure, Unleash live transforms drone and CCTV feeds into actionable intelligence. Attendees will gain insights into key design decisions and learn how cloud-based AI optimises operations, reduces risk, and unlocks the speed that modern physical AI demands.
Building an agent that works once is easy; building an agent that works reliably for thousands of users is an architectural challenge. This session bridges the gap between experimental notebooks and deployed systems, focusing on the specific engineering disciplines needed for success. Join us to learn practical strategies for: 1. System Design: architecting decoupled, scalable agent backends from day one. 2. Continuous Evaluation: moving beyond "vibes-based" testing to metrics-driven evaluation suites that ensure reliability. 3. DevEx & Tooling: streamlining the developer experience to tighten feedback loops and ship improvements faster using open-source frameworks.
New Zealand Unicorn agritech startup Halter is revolutionizing dairy farming with AI-powered smart collars that predict critical livestock events. Their machine learning models enable heat detection, calving prediction, pasture optimization, and animal behavior classification, processing data from thousands of GPS-enabled collars across remote farms. By leveraging AWS infrastructure, Halter's engineering team built scalable ML pipelines that help farmers make data-driven decisions, reduce labor costs, and improve animal welfare. Learn how Halter developed production ML models for agriculture, overcame challenges of training on livestock data, and their journey toward managed ML services.
Join Heidi Health and AWS's Generative AI Innovation Center (GenAIIC) for a behind-the-scenes look at building and deploying custom speech-to-text AI for healthcare. Learn hard-won lessons and a practical blueprint: curating domain-specific training data, fine-tuning open-weight models, validating non-deterministic outputs at scale, and shipping to production with optimized inference. Both teams share how AWS services reduced infrastructure complexity, accelerated iteration cycles, and scaled custom models across diverse real-world use cases — all while maintaining security and cost efficiency. Ideal for ML engineers, data scientists, and technical leaders exploring fine-tuning and production ML on AWS.
The agents invasion into the software market is a fact of life now. Agents are changing how we are consuming software, services and information. But just like any technological inflection point, theres a redistribution of power with and SaaS platforms are struggling to find their centre of gravity in this new world. In this talk we will explore how, Cartesian is helping platforms lean in to their strategic assets like access to customers and privacy and find their moat in the agentic age by distributing and monetizing 3rd party agents.
Most security tools find the problem and hand it to a human. Plerion closes the loop. In this talk, we'll show how Pleri, our AI security engineer powered by Amazon Bedrock, takes a critical cloud risk from detection to remediation without the alert-ticket-backlog cycle. Watch a top risk get prioritized, a ticket filed, a PR opened, and code-level remediation land in your environment. Re-define what it means to have an AI teammate that does the work, not just alerts and reporting.
Scams are a global epidemic costing businesses and consumers trillions. Apate AI turns the tables on fraudsters by deploying lifelike conversational AI agents, powered by Amazon Bedrock and speech models on Amazon SageMaker bidirectional streaming, that engage scammers in real time to detect, divert, disrupt, and decode their tactics. In this session, learn how Apate AI converts every scam interaction into actionable intelligence and how to build your own voice AI agents on AWS.
Generative AI is the largest disruption to software company business models since the emergence of SaaS. In this workshop we'll cover best practices software companies use to take AI-native products from pilot to production, including identifying use cases that drive business value, features that accelerate adoption and pricing strategies that result in profitable growth. This will include an interactive session - so bring your ideas and collaborate with other startups to help find generative AI features that add value to your product
How RedOwl Built Real-Time Financial Governance and Control on AWS: RedOwl is a real-time governance and control platform that enforces policy before a single dollar moves combining agentic AI and pre-transactional intelligence to give CFOs and finance leaders the control to turn finance into a proactive business enabler. This session unpacks the architecture behind that capability, giving technology leaders and practitioners a practical guide to deploying AI-powered financial governance that earns CFO trust and drives enterprise-wide impact.
AI agents are moving from demo to deployment. Startups across ANZ are building production-grade assistants using open-source orchestration frameworks, fine-tuned foundation models, and GPU-accelerated inference on AWS and NVIDIA infrastructure. This panel explores what it actually takes to ship agentic use casesfrom choosing the right models and frameworks to managing latency, cost, and reliability at scale. We'll hear from AirTree VC on where the investment thesis is heading, from NVIDIA on how accelerated compute is shaping the agent stack, and from Heidi Health building and scaling these systems in production. Whether it's vertical agents for healthcare, customer support, or code generation, we'll focus on what's working, what's hype, and where the real startup opportunities lie in the agent ecosystem.
We've all experienced itthat moment when an AI assistant creates more problems than it solves because of its robotic responses and lack of contextual awareness. It operates in a vacuum, making customer experiences less than delightful. In this session, you will learn how to create meaningful and hyper-personalized customer experiences with Amazon Nova Sonic and design patterns to enable new use cases. You will discover how Amazon Nova Sonic's tool use and function calling capabilities enable integration with external APIs and internal and external data sources to provide context that makes for delightful voice-based customer interactions.
Prompt-and-pray development doesn't scale. Learn how startup engineering teams are adopting Kiro's spec-driven, agentic approach to go from requirements to working code on AWS with real adoption patterns, pitfalls, and measurable productivity impact.
What if every small business could afford a chief of staff that never sleeps In this session, WhiteHorse AI shares how they build autonomous AI agents — "AI employees — that handle invoicing, email triage, lead follow-up, and customer inquiries 24/7.
Most AI agent projects stall when moving from prototype to production. This session tackles the top challenges builders face when deploying agentic AI at scale. You'll learn how to answer the fundamental question of whether to build custom agents or leverage pre-built agents for DevOps, security, development, and business productivity use cases. Then you'll discover how to address the critical production challenges of reliability, observability, cost management, security, and evaluation. Drawing from real customer deployments and AWS's portfolio of agentic AI capabilities, you'll gain actionable approaches for building agents that don't just demo well but ship and scale.
As API costs for general-purpose LLMs rise, relying solely on off-the-shelf models can quickly undermine both cost control and system reliability. In this session, we share how Nearmap moved beyond API dependency by fine-tuning and distilling domain-specific models on AWS to analyze 300 million building permits for roof modifications. Well discuss our approach to generating and structuring training data, distilling large models into smaller, production-ready alternatives, evaluating trade-offs across model architectures, and making data-driven accuracy-versus-cost decisions before deployment. Attendees will leave with concrete patterns for shipping efficient, specialized models into production.
AI agents offer powerful capabilities — and introduce fundamentally new risks that require more than traditional controls. This session explores responsible agentic AI through three lenses: the science, the framework, and a real-world customer story. Understand the scientific frontiers that make agents different — from emergent behaviour and agent-to-agent trust to the challenges of governing systems that plan, negotiate, and act autonomously. Learn the four areas of the AWS Responsible AI framework where agents change the rules, and hear how one of Australia's leading health insurer is putting responsible AI into practice — from strategy to governance to real-world trade-offs.
Application security teams face an impossible challenge: scale security expertise across growing application portfolios while maintaining development velocity. Traditional approaches force organizations to choose between speed and security. In this session, discover how AWS Security Agent transforms application security from reactive to proactive through AI-powered automation. Learn how this frontier agent conducts automated security reviews customized to your organizational requirements and delivers on-demand penetration testing tailored to your applications. Join us to see how you can scale security coverage and prevent vulnerabilities early in the development lifecycle while maintaining the speed of modern development.
Most of us spend more time hunting for information than using it. Amazon Quick changes that. It reaches across all your company's data — documents, databases, emails, Slack threads, dashboards, Jira tickets — and lets you search it, ask questions, and take action, all from one place. Available across web, mobile, Slack, and Microsoft tools with multi-model intelligence, Quick delivers consumer-grade AI with enterprise-grade security and governance. No vendor lock-in, no siloed copilots. Just one AI teammate that works wherever you do.
Woodsides Agentic Maintenance Framework connects frontline execution to longhorizon strategy, turning each job into fuel for continuous improvement. The approach uses governed evidence and multiagent AI to assemble the right context at the decision pointimproving request quality, planning accuracy, and execution readinesswhile capturing planvsactual signals that strengthen backlog quality, scheduling confidence, and longterm maintenance strategies. The result is a closed loop where execution improves strategy, and strategy improves execution, all within existing governance and systems of record. In this talk, well share practical lessons from designing the tactical layer (Maint Assist) and the strategic layer (Maint Intel), show how evidence is created once and reused across the lifecycle, and outline a maturity path from prompts to agentic orchestrationfocused on safety, reliability, and efficiency.
CBA is achieving operational excellence by harnessing the power of the AWS DevOps Agent, part of AWS's new Frontier Agents. In this session, discover how CBA is using AI-driven automation to streamline incident response, reduce operational friction, and strengthen resilience across critical systems. We'll discuss CBA's cloud transformation journey and operational challenges, explore the DevOps Agent implementation including architecture, integration, and user journeys, and share results and business impact with real-world metrics. You'll see how automated remediation, and proactive insights are helping teams move faster with greater confidence. Join us to discover how CBA is shaping a future where operations are smarter, safer, and built for scale.
Experience the ultimate AI showdown from your theater seat as finalists from the AWS AI League: Agentic AI challenge battle head-to-head in real-time. Watch top performers compete in a live, tournament-style competition where their AI agents navigate complex challenges, demonstrating the power of intelligent automation and decision-making under pressure. This electrifying viewing experience offers AI practitioners and enthusiasts unique insights into orchestrating intelligent agents using Amazon Bedrock AgentCore. See firsthand how agents handle real-world scenarios including code execution, web browsing, content moderation, and multi-step problem solvingall while competing for championship glory. The 1st place winner will represent Australia at the 2026 AWS AI League Championship at re:Invent 2026.
Building intelligent AI Agents with Amazon Bedrock AgentCore Dive into the future of Al in this competitive workshop where you'll create intelligent agents using Amazon Bedrock AgentCore. Using our no-code Ul interface and generative AI you will develop agents and agentic tools that tackle real-world technical challenges. Experience hands-on learning through dynamic gameplay with live leaderboards while mastering prompt engineering, safety guardrails, tool creation, and performance optimization. Whether you are an avid Al developer or an architect eager to gain practical experience with production-grade agentic Al, this session will give you a new hands-on experience.
AI agents offer powerful capabilities — and introduce fundamentally new risks that require more than traditional controls. This session explores responsible agentic AI through three lenses: the science, the framework, and a real-world customer story. Understand the scientific frontiers that make agents different — from emergent behaviour and agent-to-agent trust to the challenges of governing systems that plan, negotiate, and act autonomously. Learn the four areas of the AWS Responsible AI framework where agents change the rules, and hear how one of Australia's leading health insurer is putting responsible AI into practice — from strategy to governance to real-world trade-offs.
AI agents offer powerful capabilities and require thoughtful design to help manage risks. This session explores responsible agentic AI implementation with appropriate controls and governance. Understand some of the scientific frontiers that inform design considerations, including the language of AI agents, context management, agent interactions, and common sense reasoning. Learn approaches for human oversight, risk mitigation, evaluation methods, and control mechanisms to help align agent behaviors with organizational goals, and help make agentic AI both effective and trustworthy.
An unparalleled level of interest in generative AI and agentic AI is driving organizations to rethink their data strategy. While there is a need for data foundation constructs such as data pipelines, data architectures, data stores and data governance to evolve, there are business elements that need to stay constant like cost-efficiency and effectively collaborating across data estates. In this session we will cover how building your data foundation on AWS provides the tools and the building blocks to balance both needs, and empower organizations to grow their data strategy for building AI-ready applications.
Existing SaaS providers must determine how and where agents best fit into their offerings. Getting there requires organizations to transform existing IP and functionality into agent-powered experiences. This breakout will dig into the details of this transformation, examining the patterns, strategies, and techniques that can be used to introduce agents into an existing multi-tenant system. Well focus heavily on identifying the target agents, digging into how/where theyre built and introduced, how theyre integrated, and so on. Well also dig into how multi-tenancy lands in new agents, integrating with MCP servers, using RAG, applying tenant isolation, supporting onboarding, and on on.
Confused by inbound vs. outbound authentication for agents You're not alone. This Level 300 session demystifies OAuth flows and agent identity patterns through the lens of a practitioner's learning journey. Explore the differences between SPA (single-page web app) and agent authentication, then dive into AgentCore's inbound/outbound auth with Runtime and Gateway. Through live code demonstrations of 3-legged OAuth flows, you'll see exactly how agents authorize actions on behalf of users. Leave with working code examples from aws-samples and practical implementation insights to accelerate your agent development. Part of the AgentCore session track.
Join this session to explore how Amazon EKS Hybrid Nodes enables GenAI inference anywhere. We'll discuss reference architectures for adding on-prem GPUs to your EKS hybrid cluster, and for running real-time data capture and processing at the edge. You'll learn how EKS Hybrid Nodes enables seamless integration between the cloud and your on-prem or edge environments. Well also walk through a real-world example, showcasing how to accelerate GenAI inference at the edge using Amazon EKS Hybrid Nodes with NVIDIA DGX platform.
Every network design decision involves careful trade-off considerations. In this session, master the art of making critical network design decisions through real-world scenarios that showcase Megaport's innovative NaaS platform for AWS connectivity. Learn how to evaluate key trade-offs between centralized and distributed architectures while balancing security, performance, and cost requirements. Explore how Megaport's on-demand bandwidth, private connectivity to AWS Direct Connect, and multi-cloud capabilities transform network design decisions. Whether you're building a global network, managing multi-account environments, or implementing hybrid connectivity to on-premises locations, attendees will leave with actionable insights and practical decision-making tools to optimize network infrastructure architecture designs with Megaport and AWS
Essential services that power global economies and critical infrastructure demand exceptional resilience. Through nearly two decades of focused innovation, AWS has developed core engineering practices and operational approaches that power critical workloads worldwide. Explore how AWS's architectural innovations and organizational practices help customers build robust services that maintain resilience during severe disruptions. Learn how AWS's continued investment in resilience provides the foundation for delivering essential services across governments, economies, and critical infrastructure.
In this session, learn about AWS Lambda's execution environment lifecycle, diving deep into how the service manages isolation at the function level, and understanding the security implications of environment reuse patterns. Learn about traditional patterns for compute isolation in multi-tenant environments, as well as explore Lambda's tenant isolation mode - a new powerful capability that enables tenant-level compute separation without operational overhead. Explore how to implement robust tenant isolation strategies, manage state across executions, and leverage Lambda's security boundaries effectively. Whether building new SaaS applications or enhancing existing ones, leave with practical knowledge to implement secure multi-tenant architectures at scale.
Not all disaster recovery strategies can address the complex, dynamic nature of modern cloud infrastructures, leading to gaps in system resilience and compliance adherence. Discover how to enhance resilience and disaster recovery on AWS empowered by AI. This approach bridges infrastructure insights and application-level testing, enabling more effective disaster recovery preparation. You will learn how to leverage Large Language Models (LLMs) with AWS Resilience Hub and AWS Systems Manager to modernize testing, analyze infrastructure, and generate targeted AWS Fault Injection Service experiments and recovery runbooks. Walk away with practical examples of automated test generation with templates and learn to design prompts.
In this session, we will walk through the architecture for the Amazon DynamoDB DNS management system that triggered the service disruption on October 20, 2025. We will share the lessons that the DynamoDB team learned from this event and explain how we are using these insights to improve both DynamoDB and AWS. You will walk away with actionable knowledge that you can apply to the systems you build.
Secure Multi-tenant SaaS with AWS Lambda: A Tenant Isolation Deep DiveIn this session, learn about AWS Lambda's execution environment lifecycle, diving deep into how the service manages isolation at the function level, and understanding the security implications of environment reuse patterns. Learn about traditional patterns for compute isolation in multi-tenant environments, as well as explore Lambda's tenant isolation mode - a new powerful capability that enables tenant-level compute separation without operational overhead. Explore how to implement robust tenant isolation strategies, manage state across executions, and leverage Lambda's security boundaries effectively. Whether building new SaaS applications or enhancing existing ones, leave with practical knowledge to implement secure multi-tenant architectures at scale.
Accelerate your VMware migration journey with AWS Transform, the first agentic AI service for large-scale VMware workload migrations to Amazon EC2. Discover how to migrate from on-premises VMware infrastructure to a modernized, cloud-native architecture while overcoming challenges like evolving licensing models and vendor lock-in. Meet the team behind AWS Transform and see a live demonstration showcasing automated application discovery, dependency mapping, network translation, wave planning, and server migration with optimized EC2 instance selection. Learn practical approaches to streamline large-scale migrations and modernize VMware workloads to AWS with greater speed and confidence.
In this code-first session, we demonstrate how to add agentic AI capabilities and augment a legacy application using Amazon Bedrock AgentCore and the Amazon Strands Agents SDK. We will explore how to build AI-powered features for a legacy application without modifying the existing backend code. We will showcase how to leverage existing APIs and Lambda functions as the backbone for your agentic AI experience. You'll learn how to execute code in isolated sandbox environments, ensuring security while accessing internal data sources with Amazon Bedrock AgentCore Code Interpreter.
Your legacy applications and infrastructure don't have to be a liability. In this session, discover how leading enterprises are converting tech debt into modern cloud advantages that unlock AI capabilities, cut costs, and accelerate innovation. The path to AI starts with migration and modernization. We'll walk through the complete transformation journey: infrastructure, applications, data, and AI-ready business outcomes. You'll see how new agentic AI automation is making migration and modernization faster, simpler, and more cost-effective. We'll explore proven pathways for your most critical workloads (Microsoft, VMware, SAP, and mainframe), backed by 20 years of AWS expertise.
Discover how customers are leveraging AWS AI-driven solutions to accelerate their cloud transformation journey, moving beyond traditional migration and modernization to achieve digital transformation excellence. This session showcases real-world experiences where organizations have integrated AI-powered accelerators with AWS cloud services to achieve 3x faster migration timelines and drive unprecedented business value. Learn actionable strategies and see demonstrations of how a large transformation project can become a digital enterprise enabler for your organization,
Rio Tintos data science team saw an opportunity to preserve institutional knowledge and improve developer productivity by modernizing a legacy codebase. Rather than attempting a full system overhaul, the team focused first on adding generative AI capabilities to their critical legacy application. By using the proven, open, and trusted data foundation of AWS, the company laid the groundwork for incremental modernization without disrupting core operations. Learn about model fine tuning against legacy codebases, Amazon Nova, SageMaker Jumpstart and AgentCore in this deep dive with AWS & Rio Tinto
Want to cut your Microsoft licensing costs by up to 70% while modernizing SQL Server workloads Join us to explore AWS Transform's groundbreaking
This session demonstrates how agentic AI systems revolutionize legacy application modernization through intelligent reverse engineering workflows. We showcase a multi-agent architecture that autonomously analyzes legacy codebases, generates comprehensive business specifications, and rebuilds cloud-native applications while preserving critical business logic. Our agentic framework orchestrates specialized AI agentsAnalyzer, Generator, Evaluator, and Refinerworking collaboratively to extract institutional knowledge from decades-old systems and validate modernized applications against original code. Drawing from real-world enterprise implementations including Commonwealth Bank of Australia's transformation, we present practical patterns for deploying autonomous AI agents that achieve 70% efficiency gains in modernization cycles.
Ciaran Hale shares how Deputy moved from fragmented AI experiments to a centralised AI and data foundation on AWS. By standardising infrastructure, introducing governance guardrails, and building reusable components, Deputy enabled teams to scale AI with confidence. This shift also transformed internal adoptionembedding AI into everyday workflowsand unlocked new customer value through Deputy AI, delivering smarter automation and insights in-product. A practical blueprint for building an AI-native organisation.
Learn how AWS zero-ETL integrations eliminate complex data movement pipelines across multiple database engines, enabling data engineers, architects, and DBAs to reduce maintenance overhead while ensuring near real-time data availability for analytics and ML workloads. Examine the underlying architecture for supported zero-ETL integrations between Amazon Aurora, Amazon DynamoDB, and Amazon RDS sources to Amazon Redshift, Amazon SageMaker, and Amazon OpenSearch Service targets. Explore data movement options, tunable settings, and monitoring capabilities for ongoing data replicationall without traditional ETL complexity.
Powering your Agentic AI experience with AWS Streaming and MessagingOrganizations are accelerating innovation with generative AI and agentic AI use cases. This session explores how AWS streaming and messaging services such as Amazon Managed Streaming for Apache Kafka, Kinesis Data Streams, Amazon Managed Service for Apache Flink, and Amazon SQS build intelligent, responsive applications. Discover how streaming supports real-time data ingestion and processing, while messaging ensures reliable coordination between AI agents, orchestrates workflows, and delivers critical information at scale. Learn architectural patterns that highlight how a unified approach acts on data as fast as needed, providing the reliability and scale to grow for your next generation of AI.
Learn how to optimize Apache Iceberg data lakes on Amazon S3 for cost-effectiveness while enabling real-time analytics. This session explores S3 Tables deployments, focusing on streaming data from Apache Kafka via Amazon MSK into Iceberg format. Discover practical approaches for real-time table maintenance, metadata optimization for high-velocity writes, and data compaction strategies. Implement cost-effective retention policies using S3 Lifecycle configurations while maintaining sub-minute data freshness. See how MSK's native Iceberg integration eliminates pipeline overhead, reducing latency and operational costs. Gain actionable insights for balancing streaming performance with cost optimization at scale.
Discover how Melbourne-based Easygo, powering Stake and Kick.com, transformed their data analytics infrastructure to process over 600,000 daily transactions and tens of millions of streaming events. Learn about their implementation of a modern lakehouse architecture combining Amazon Aurora Zero-ETL integration with Amazon Redshift, Amazon Kinesis with AWS Glue streaming, and Apache Iceberg on Amazon S3. Results include 95% faster queries, 80% fewer ingestion incidents, 9 hours weekly maintenance savings, and accelerated global expansion. Explore practical strategies for building scalable, secure data foundations delivering near real-time analytics with robust governance across regulated markets.
Join this session to learn about the latest capabilities in Amazon SageMaker Catalog that help organizations govern data and AI more effectively. We will walk through new features that make it easier to discover, govern, and securely share structured and unstructured data, models, business intelligence dashboards, and applications. Youll hear how customers are using these capabilities to improve data discovery and access, streamline compliance, and support AI initiatives.
Agentic AI Transforming Quality at Cloud SpeedFinancial services cloud transformations unlock tremendous opportunity - and quality assurance is the catalyst. The Quality Validation Agent Framework deploys specialised AI agents across the delivery lifecycle, collaborating through the AgentCore Runtime Platform to continuously monitor, validate, and accelerate work in real-time. Covering Assessment, Transformation, Testing, and Deployment Intelligence, these autonomous agents shift FSI organisations from reactive checkpoints to proactive validation - eliminating rework, detecting defects early, and achieving AWS Well-Architected compliance with confidence. Come and join us to discover how agentic AI turns quality assurance into your fastest path to production in banking and financial services!
Commonwealth Bank migrated the world's largest SAP core banking deployment to AWS in 18 months: the system behind 40% of Australia's payments, 15 million customers, running 247. This isn't a lift-and-shift story, it's a reinvention of how the bank runs critical systems - from architecture and resilience engineering to replacing siloed operational teams with full-stack automation, and the cultural shift this required. Join us to hear how CBA's critical financial infrastructure was modernised with AWS, and what this unlocks for their AI-enabled future. If you're building foundations for regulated, mission-critical workloads, this is the session you don't want to miss.
From enterprise data mesh to AI with Amazon SageMaker Unified StudioFinancial institutions are unlocking enormous value with AI agents — from personalised customer experiences to better risk decision making. But to deliver on that promise, agents need data they can find, understand, and trust. This session shows how a data mesh architecture on Amazon SageMaker Unified Studio builds that foundation: discoverable data across lines of business, business context that grounds agent responses in real meaning, quality signals that build confidence in every answer, and governed access that keeps you compliant by design. We cover domain ownership, multi-account strategies, data contracts, business glossaries, data quality, and cross-domain governance — and demonstrate how this foundation empowers agentic AI that delivers trusted, accurate results at enterprise scale.
Getting agentic AI right in financial services means balancing innovation with the realities of compliance, risk, and auditability. This session cuts through the hype — exploring proven architectural patterns from reactive agents to multi-agent topologies, and how FSI organisations are using them to transform customer experience and automate operations. Leave with actionable guidance on building the business case, avoiding enterprise-scale pitfalls, and putting well-architected agents into production.
Australian Payments Plusoperator of Australia's critical payment infrastructure including eftpos, BPAY, and NPP, processing millions of daily transactionstransformed their development practices by adopting Spec-Driven Development using AWS Kiro. AP+ manages the payment rails connecting banks, merchants, and consumers throughout Australia. Through intensive Event-Driven Architecture bootcamps and hands-on training, engineering teams now independently run development workshops every two weeks, accelerating delivery of payment platform innovations while maintaining the highest security and compliance standards required for national financial infrastructure. Learn the practical framework for building development velocity in regulated environments.
In this session discover how HBF revolutionized claims processing using AWS. By leveraging Amazon Bedrock and Amazon Textract, they cut claim costs from $2 to just 10 cents and reduced the processing time from two weeks to two minutes. With accuracy in the high 90s and 70,000 claims processed monthly, their end-to-end AI-powered architecture for claims processing sets a new benchmark for speed, cost, and customer satisfaction.
Dive deep into advanced security architectures for AI workloads, exploring how to protect your workload against sophisticated attack vectors. Through technical examples, we'll implement secure architectures for AI workloads, covering identity, fine-grained access policies, and secure foundation model deployment patterns. Learn how to harden generative and agentic AI applications using AWS security capabilities, implementing least-privilege controls, and building secure architectures at scale.
Get up to speed on emerging threat actor tactics and techniques across the attack chain. In this session, we'll expound upon methods of Initial Access, Persistence, Defense Evasion, Lateral Movement, and Impact. You'll gain practical knowledge of specific configurations to detect and mitigate these threats, and learn common misconfigurations to avoid.
Dive deep into advanced security architectures for AI workloads, exploring how to protect your workload against sophisticated attack vectors. Through technical examples, we'll implement secure architectures for AI workloads, covering identity, fine-grained access policies, and secure foundation model deployment patterns. Learn how to harden generative and agentic AI applications using AWS security capabilities, implementing least-privilege controls, and building secure architectures at scale.
Downtime costs revenue. Alert fatigue burns out your best engineers. Manual incident investigation wastes hours that could be spent building. Every cloud team faces these operational challenges, yet most still rely on tribal knowledge and context-switching across multiple tools to diagnose issues. In this session, we demonstrate how AWS DevOps Agent transforms incident response from hours of manual investigation to minutes of autonomous analysis. Watch as the agent automatically correlates data across your observability tools, identifies root causes, and delivers actionable mitigation plans freeing your team to build instead of firefight.
Research papers hold ideas you won't find in any docs, blog posts, or explainer videos. They're also brutal to read, and can leave you frustrated. This talk is about how to actually read one, layer by layer. First what the paper is about, then why it's important, and finally how it works. We'll start with AWS IAM Access Analyzer and it's paper on Stratified Predicate Abstraction. Then we'll work backwards through the research papers it's built on, learning about SMT solvers and Decision Procedures. You'll walk out with a method you can use on any paper, in any field.
Major events produce fragmented data across CCTV, sensors, ticketing, and venue systems. PMY Group will show how Optic, built on AWS, brings these sources together to create real-time crowd intelligence. Using the Australian Grand Prix as a case study, this session explores how operators gained live visibility into movement and congestion to support faster operational decisions. It also highlights how the same AWS foundation can support scalable analytics and broader unified data outcomes across venues and events.
Traditional AI-assisted development treats AI as a tool. The AI-Driven Development Lifecycle (AI-DLC) treats it as a central collaborator throughout the development process. In this session, join Skyjed CTO Stephen Brown, to share how his team applied AI-DLC to compress a 4-6 week implementation into 48 hours. Discover how AI-DLC's three phases — Inception, Construction, and Operations — reimagines the software lifecycle through AI-powered execution with human oversight and dynamic team collaboration. Drawing on Skyjed's firsthand experience on integrating AI-assisted development into their existing software development lifecycle, this talk explores how team collaboration, Kiro-powered workflows, and enterprise-grade code development practices were enhanced rather than replaced. You'll walk away with practical steps to achieve 1520x accelerationwithout sacrificing quality, governance, or control.
AAMC partnered with AWS to build an intelligent, AI-driven contact centre that transforms data into actionable insights. The solution unifies customer interaction datacalls, chats, surveys, and QA reviewsinto a single environment where AI continuously analyses and learns. Leaders ask questions in natural language and receive instant, data-backed answers with visual context. This self-optimising system enables faster, more confident decision-making while continuously improving customer experience operations through deeper visibility and adaptive learning capabilities.
Healthcare company, Blackmores, accelerated their SAP RISE program by utilising Experience Based Acceleration (EBA) to build a production-ready AWS Landing Zone with Terraform in two days using Kiro.
Fingermark's Eyecue platform turns drive-thru video feeds into real-time operational intelligence for some of the world's largest QSR brands. Using hybrid edge-cloud architecture on AWS, they track every customer journeycapturing precise timing at order points, windows, and bayswhile keeping sensitive data at the edge. Now they're taking the next leap: agentic AI powered by Amazon Bedrock AgentCore. Autonomous agents automatically answer compliance questions"Are there spills Are staff following food handling protocols"replacing manual audits with continuous monitoring. See how a Kiwi company scaled from local innovation to global impact, and from computer vision to autonomous agents.
Deploying ML in high-stakes environments demands enterprise readiness, governance, and continuous monitoring. In this session, you'll learn how Gold Coast Health moved from pilot to production with a predictive model identifying patients unlikely to attend procedures — achieving 33% precision, doubling the 15% manual baseline — while ensuring fairness across cohorts. The session covers real-world ML architecture on Amazon SageMaker Pipelines, production monitoring including data quality, pipeline health, and drift detection, plus navigating AI governance through bias analysis and impact assessment. Whether you're in healthcare, financial services, or any regulated industry, walk away with actionable patterns for deploying responsible ML at scale.
In today's data-driven healthcare landscape, organisations must rapidly transform diverse data sources into actionable insights that improve patient outcomes and accelerate operational efficiency. This session showcases how AWS' integrated analytics capabilities can deliver unmatched price-performance for every analytics workload, from data processing and SQL analytics to streaming and business intelligence. Through real-world healthcare examples, learn how AWS' built-in governance and scalability enable organisations to build secure, efficient analytics pipelines that accelerate time-to-insight. Ideal for data practitioners, IT decision-makers, and executives evaluating enterprise analytics platforms to drive their data-driven transformation.
Join us for an in-depth case study on Safe Transport Victoria's successful use of Cloud to modernise, streamline and save costs while moving from on-premises infrastructure to AWS Cloud. This session will demonstrate how a small Regulator has added resilience to their safety outcomes, including to those Victorians with accessibility and mobility needs achieved modernization while maintaining service continuity and reliability.
Autonomous AI systems that plan, decide, and act across workflows are transforming how organisations deliver mission-critical services. This session shares security-first architecture best practices for designing, deploying, and governing agentic AI in high-assurance environments, drawing from Australia's Information Security Manual (ISM) and AWS security frameworks. Discover practical patterns for architecting proactive, intelligent services while maintaining security, transparency, and operational resilience through defense-in-depth strategies and purpose-built AWS capabilities.
As governments worldwide race to modernise services, agentic AI based autonomous systems that plan, decide, and act across workflowsis emerging as a game-changer. This session delivers a compliance-first blueprint for designing, deploying, and governing agentic AI in the Australian public sector, fully aligned with Australias Information Security Manual (ISM) and national AI standards. Learn how to transform legacy processes into proactive, citizen-centric services while ensuring security, transparency, and trustwithout regulatory risk.
Every month, Service Stream's field operations generate over 1 million images requiring verification — proof that infrastructure maintenance work has been completed to contract specification. Manually reviewing this volume was resource-intensive, error-prone, and created payment bottlenecks that slowed contractor payment cycles and strained client relationships. To solve this, Service Stream partnered with AWS to build an AI-powered work order verification system. The system now processes up to 800 work orders per hour — 27 times faster than manual review — with improved accuracy, reduced subjectivity, and no increase in headcount. In this session, learn how Service Stream used AWS AI and cloud services to automatically check field images against contract requirements — delivering a production-ready solution in just three months. We'll walk through the business drivers, solution design, and real-world outcomes — including how eliminating manual bottlenecks improved ServiceS tream's ability to meet client commitments, reduce payment delays, and build trust across their contractor network. Whether you're in field services, utilities, infrastructure, or any operations-heavy industry, this session will show you how intelligent automation can transform high-volume verification workflows and deliver tangible business value.
Join Tim Sheridan, Director of Product & Technology at Seven West Media, as he shares how Seven is leveraging cloud and AI to maximise the return on their most valuable asset — premium live content. With marquee events like the AFL Grand Final and The Ashes cricket series, the stakes couldn't be higher: massive concurrent audiences, critical advertising revenue, and zero tolerance for failure. Tim shares how they leaned on AI-powered developer and business tools to accelerate delivery, de-risk high-profile events, and maximise the return on its premium content investments. Discover how Seven's team transformed their approach to innovation — using cloud-native architecture and AI to achieve speed to market, audience experience, and advertising revenue.
For media and communications organizations, the ability to rapidly discover, repurpose, and distribute content across platforms directly impacts revenue and audience engagement. This session examines how Generative AI is transforming content operations through intelligent metadata extraction, semantic search, and automated workflow orchestration. Using a case study from a global media organization managing 13 petabytes of content growing at 3,000 hours daily, we'll explore practical implementations using Amazon OpenSearch for multimodal retrieval, Amazon Neptune for knowledge graphs, and agentic AI for content assembly. Learn how organizations are achieving faster time-to-market, improved content monetization, and enhanced audience experiences through AI-powered content discovery and recommendation systems
Media advertisers see up to 25% higher engagement when delivering custom creative to relevant audiences, yet producing quality video ads traditionally requires weeks of expensive and specialized expertise. Discover the inner workings of Amazon Ads new AI Creative Agent, and how it's transforming the creative process by automating and enhancing the generation of multi-format ads to businesses regardless of their size or creative expertise. Explore how Amazon Bedrock, custom-built ML models, GPUs, and model evaluations are used to orchestrate and generate compelling ad creatives into full video productions with professional voiceovers from conversational natural language, while reducing creative development time.
In this workshop you will be shown how to build functional prototypes using our proven techniques. Learn how to leverage Kiro to go beyond "vibe-coding", and transform ideas into fully functional prototypes while validating technical approaches. Discover effective spec-driven development and prompt engineering techniques combining generative AI capabilities with AWS services for rapid iteration and refinement. If participants would like to follow along please bring your own laptop.
Building AI applications that customers trust requires more than technical excellenceit demands a deliberate approach to managing risk across every stage of the AI lifecycle. As organizations scale their AI initiatives, the challenge of balancing innovation speed with responsible AI practices across dimensions like privacy, security, fairness, safety, and explainability becomes increasingly critical. Join our panelists for a 30-minute discussion where they will explore: Practical approaches to embedding responsible AI principles into AI application development without slowing down innovation, key considerations across privacy, security, fairness, safety, and explainability that organizations should prioritize, lessons learned from building AI applications that earn and maintain customer trust, and strategies for navigating the evolving responsible AI landscape and managing risk at scale. Whether you are a technical leader building AI solutions, a business decision-maker shaping your organization's AI strategy, or a practitioner looking to deepen your understanding of responsible AI, this session will provide actionable insights to help you build AI applications that are not only innovative but also trustworthy.
As AI reshapes every industry, professionals across all roles and backgrounds are navigating an unprecedented pace of changebringing new opportunities but also rising burnout, blurred boundaries, and pressure to continuously adapt. This moment of disruption presents a powerful opportunity to not only deliver innovation but to redesign how we lead, build culture, and sustain meaningful careers in more equitable ways. Join accomplished AWS leaders and peers for this immersive session that combines strategic leadership frameworks, emotional intelligence, and interactive roundtable discussion to accelerate your impact in tech. Together, we will explore practical strategies for claiming visible technical leadership, activating professional networks, setting sustainable boundaries in hybrid work, and championing responsible AI adoption without amplifying existing inequalities. Participants will share lived experiences, tactics that worked and lessons learned, and build meaningful connections through guided speed networking in a collaborative, supportive environment. This session empowers professionals from all backgrounds, with particular focus on amplifying diverse voices and fostering inclusive innovation. Leave with actionable strategies to strengthen your leadership presence, leverage emotional intelligence as a career accelerator, build psychologically safe and inclusive team environments, and navigate the challenges shaping your future in tech.