StoreSteadyStoreSteady
Output governance

LLM Output Governance

StoreSteady uses LLMs to render bounded merchant copy from evidence. The model is not treated as the source of truth.

Renderer, not source of truth

A model can draft a clear explanation, but the finding must be grounded in structured evidence, source URLs, scan observations, confidence, and validation requirements.

Required inputs

Evidence payload

The source page, structured data field, policy excerpt, channel response, AI observation, or connected merchant source used for the finding.

Finding type

The issue family and merchant-facing consequence that determine the shape of the explanation.

Confidence and validation

The confidence label and the retest path that bound how direct the recommendation can be.

Repair and fallback

Generated copy that drops evidence, overstates certainty, invents outcomes, or loses the validation path should be repaired or replaced by deterministic copy.

Private boundary

StoreSteady publishes the governance principles and public policy shape. It does not publish internal prompts, full evals, exact thresholds, scoring weights, repair logic, adversarial tests, or vendor-specific prompt details.