AuditAI: six agents, governance, and measured automation

Shipping multi-agent workflows inside a regulated nonprofit — alignment with Auditing, engineering, and General Counsel.

AuditAI started as a discovery bet: could we chain specialized agents over repetitive audit workflows without bypassing human judgment? The product answer was yes — but only with explicit handoffs, logging, and sprint-level alignment with legal stakeholders.

We treated each agent as a narrow worker: intake, classification, draft generation, and routing — orchestrated so humans stayed in the loop for edge cases and policy-sensitive outputs.

Impact was measured on agreed slices of work: roughly ~30% automation on common paths and ~50% reduction in manual labor time on those slices. The numbers matter less than the definition of what we counted; we documented that with audit leadership so outcomes were interview-defensible.