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.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Three-stage agent rollout. Claude Code on Bedrock for devs → OpsGorilla (200+ employees, Slack-integrated) → Roni AI (customer-facing SMSF compliance, days → hours).
Why it matters
A repeatable pattern: dev tools → internal ops → customer-facing. Each stage banks confidence for the next.
The hard parts
Customer-facing agents have compliance and liability stakes that internal tools don't. The leap is real, not incremental.
Playbook moves
(1) Bank confidence with internal tools first. (2) Customer-facing requires legal and compliance review as a gate. (3) Run dual-key approval for first 90 days of customer-facing.
The surprise
Roni AI's "days to hours" for SMSF compliance is the kind of vertical-specific gain where fine-tuned, domain-aware approaches beat general agents by an order of magnitude. Generic agents wouldn't get there. Vertical specialisation beats horizontal scale here — and probably in most regulated workflows.
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Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
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