Regression Radar

An idea — no code yet — for a service that watches your LLM app's real traffic, auto-generates an eval suite from it, and alerts you when a prompt or model swap quietly makes output worse. Usage-based pricing model is part of the pitch.

The problem is real and painfully familiar: teams ship a prompt tweak or bump a model version and find out weeks later, from a customer, that quality slipped. Framing evals as something derived automatically from production traffic — rather than a test suite someone has to hand-write and maintain — is the right wedge, and usage-based pricing fits how LLM spend is already budgeted. What you're buying here is the framing and category read, not an asset: there's no code, so verify how much of the thinking is written down (schemas, alerting logic, the grading approach) versus living in the seller's head, and go in knowing you'll be competing with LangSmith, Braintrust, Arize and similar for the same buyer. Treat it as a cheap head start on a thesis you were probably going to explore anyway — the hard part, deciding what 'quality degraded' means without a human in the loop, is still yours to

Cindy's opinion, generated from this listing — including the market size, which is a rough estimate. Not financial advice; do your own diligence.