ANBD-GENESIS is a decision engine for order, refund, and signup flows. One API call returns EXECUTE, REVIEW, ESCALATE, ABSTAIN, or RECOVER — with an explicit confidence score and full audit trail. It doesn't have to decide every time: low-confidence or novel cases get escalated to a human instead of guessed. Includes HMAC-signed webhooks, CSV audit export, an official Python SDK, and multi-tenant isolation with hashed API keys. Free tier available.
Hey Product Hunt! 👋
I built ANBD-GENESIS because most "AI decision" tools force a false choice: automate everything (risky) or review everything by hand (doesn't scale).
The engine explicitly refuses to decide when it doesn't have enough evidence — it escalates to a human instead. That's not a limitation, it's the core design.
Under the hood it uses Vector Symbolic Architecture (binary hypervectors) instead of an LLM call, so it runs in ~4ms and costs a fraction of a typical AI API call — which matters when you're evaluating thousands of orders or transactions per minute, not chatting one at a time.
Would love your feedback, especially from anyone dealing with order/refund fraud review at scale. Happy to answer any technical questions below!