Agentic AI is finally moving from lab demos to the front lines of AML, fraud, credit, and model risk—yet most banks are still stitching together fragile pilots that can’t pass audit or scale beyond a few champions. This whitepaper shows AI application developers how to change that, laying out a practical, architecture-first playbook for building safe, explainable, and auditable agentic systems that plug into real KYC/AML and onboarding workflows instead of sitting on the sidelines. You’ll get concrete patterns, anti-patterns, and an implementation roadmap—from tool layers and model meshes to Agent Ops, RAG, and memory design—so your next agent doesn’t just “look clever” in a demo, but stands up to model risk, internal audit, and regulators in production.
From Smart Models to Useful Agents: How to Make Al Actually Matter at Work
One question I often hear from prospective users of our technology is where the value will come from. It won't come from larger models. Instead, it will originate from applications that are...
