From Risk Score to Financial Guarantee: Designing the Synthos Warranty

Most quality tools stop at a score. We wanted Synthos to stop at consequences: if a validation says your data is sound and it is not, we pay. Turning that sentence into a product was the most cross-functional design problem we have solved.

Eligibility is earned, not bought. A warranty can only be requested on a validation whose risk score clears our threshold — currently under 50 — because a guarantee on data we flagged as risky would be theater. Requests go through human review before coverage activates, with clear pending, approved, and rejected states.

A warranty nobody can claim against is marketing. Filing a claim from the dashboard takes a claim type — performance shortfall, collapse event, prediction error — an amount capped at the coverage limit, and a description of what happened. Coverage windows, premiums, and expiry dates are visible on every warranty card; nothing about the terms hides in a PDF.

Every claim teaches us something. A claim is, by definition, a case where our cascade said one thing and reality said another — which makes the claims pipeline our most valuable model-improvement dataset. The warranty is simultaneously a customer promise and an error-correction loop.

Once money rides on predictions, internal debates change character. Confidence intervals stop being a nice-to-have. Extrapolation edge cases get prioritized over shinier features. The warranty is the product decision that keeps every other product decision honest — which is exactly why we shipped it early instead of someday.