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Making AI features measurable, safe and dependable.
AI outputs vary, so production systems need ways to measure quality and keep behaviour within bounds. Evaluation sets test a feature against known good answers; guardrails filter inputs and outputs for safety, privacy and policy.
A set of real examples scores every change to prompts, models or retrieval.
Checks block sensitive data, unsafe content and out of scope requests.
Live quality, cost and latency are tracked so regressions are caught early.
Evaluation suites for AI features
Safety and privacy filters
Quality and cost dashboards
We build evaluation in from the first prototype, because an AI feature you cannot measure is one you cannot safely improve.
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Tell us the process or product you have in mind. We will give you a straight answer on fit, effort and risk.