Custom agent harness for autonomous suspicious-transaction (AML) flagging at banks
A small custom agent harness — not a general-purpose agent framework — that sits around a frozen frontier model and autonomously monitors bank transactions 24/7, flagging suspicious ones into suspicious activity reports for human review rather than blocking accounts itself. The harness owns the data layer: agent loop, memory layer, context engineering, and a toolbox/skillbox.
online B2B Service / Consulting / Agency
From AI Engineer — Memory-Aware Agent Harnesses for Anti-Money Laundering — Nacho Martinez, Oracle at 04:57
Problem: Human AML analysts spend enormous time reviewing transactions; LLMs alone can't run autonomously for long periods because context windows are limited and models have no inherent memory, so autonomy requires building the scaffolding yourself.
For: Mid-sized banks' compliance/fraud teams, or consultants serving financial clients
Products from this video
GitHub Codespaces OpenAI Chat Completions API Oracle Oracle Cloud Infrastructure (OCI) Oracle Database WorkshopWaitingRoom
Examples
- The workshop's own AML agent: a Grok model on OCI connected via the harness to a fake bank's transaction database, autonomously generating suspicious activity reports reviewed by a human.
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