Zero Hallucination Stack: Architecture for AI You Can Trust, by PitCrew

Most enterprise AI stalls at the same wall - the model hallucinates, fabricates citations, and gets the math wrong. Better prompts won't solve this but better architecture will. We will walk through the multi-layer stack we built at PitCrew to deploy AI agents in regulated financial services, where an incorrect number has legal consequences. Specifically, combine Model's reasoning with formal verification of agentic work, firm-specific ground truth policies that constrain what the agent can do, and an evidence chain that traces every output to its source data. Attendees will leave with a concrete architecture pattern they can apply to any domain where AI accuracy isn't optional. Not theory but production systems running daily across thousands of accounts.