Commonwealth Bank
Covenant intelligence
Policy-grounded agents for business lending.
My contribution
Architected an agentic workflow covenant recommendation system using a 4-node LangGraph DAG with parallel Covenant and Undertaking agents fed by a shared Industry Analyst agent, reducing the business loan assessment cycles from weeks to hours with fully policy-cited, Pydantic-enforced structured outputs.
Technical approach
Built a self-improving AI system where credit analyst override decisions trigger a LLM judge to extract confidence-scored patterns stored in Amazon Opensearch, retrieved as tool calls during future agent runs, compounding institutional knowledge across 20+ industry verticals and improving recommendation accuracy from 50% to 75%.
More project context
- Eliminated hallucinated financial thresholds by designing a two-tier RAG pipeline over Amazon Opensearch with table-aware chunking and re-ranking, enabling agents to cite exact policy sections rather than infer thresholds from priors.
