What should audit AI be allowed to say?
Only what it can cite. Generic chatbots invent standards and page numbers. A usable audit assistant gathers library-grounded PBC items, retrieves from uploaded workpapers, and marks unverified rows instead of dressing them as findings.
Proof: Audit Genie and ChainTech
Audit Genie is a Client Auditor stack: React SPA, FastAPI, Claude-primary multi-LLM routing, ChromaDB hybrid RAG, and a source-grounding filter. PBC gather retrieves library-only standards, asks for structured JSON, and rejects unverified line items. ChainTech AI Chat is live on chaintech.co for payments and compliance advisory with source cards next to each answer.
Fintech advisory is a cousin, not a clone
ChainTech’s problem is corridor knowledge buried in PDFs; Audit Genie’s problem is engagement discipline. Both need citations. The retrieval corpora, review UI, and liability story are different—do not paste one prompt into both products.
Related work and reading
Frequently asked questions
What is PBC in Audit Genie?
Prepared-by-client checklists. The agent gathers industry library requirements, structures them as JSON, grounds each item, and only then renders the interactive checklist.
How do you stop hallucinated audit answers?
A strict source-grounding filter keeps grounded items and rejects the rest into a fallback loop. Chat and reports retrieve from ChromaDB before the model drafts language.
Are ChainTech answers citeable in review?
Yes. Responses surface source documents so advisors and compliance reviewers can verify claims before they leave the firm.