Be ahead of the pack. Ship AI you can defend.
Tools for trustworthy AI & measurement.
Evaluation, monitoring, provenance, reproducible evidence—so you can ship with confidence and keep it that way.
Turn every release into assurance-ready evidence—before customers, auditors, or incidents force the issue.
- Assurance Packs
- Package intent, evaluations, risks, and monitoring into a shareable evidence bundle.
- Operational signals
- Catch drift, regressions, and policy violations early—with minimal, reliable telemetry.
Be ahead of the pack
Publish an Assurance Pack for every release: intent, evaluations, risks, and a monitoring plan—versioned and shareable.
Three pillars
Build an evidence trail you can defend—without slowing down your team.
Evidence packs (Assurance Pack)
Capture intended use, evaluation results, risks, and monitoring plans in a single, reviewable artifact.
Monitoring by default
Choose signals that survive outages and refactors—then make them part of release criteria.
Provenance & reproducibility
Record what ran, on which data, under which policies—so results can be reproduced and trusted.
What is an Assurance Pack?
An Assurance Pack is a lightweight evidence bundle that helps teams explain a system’s intent, validate behavior, and keep the evidence current over time.
- Intended use — scope, assumptions, and known constraints.
- Evaluation results — reproducible tests and what passed (or didn’t).
- Risk register — hazards, mitigations, owners, and review cadence.
- Monitoring plan — signals, thresholds, and escalation paths.
How it works
A simple loop: define what “good” looks like, evaluate against it, then monitor and bundle evidence as reality changes.
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1) Define
Set intended use, success metrics, and policy constraints you can test against.
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2) Evaluate
Run reproducible evaluations and record what passed, what failed, and why.
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3) Monitor / Bundle
Track live signals, detect drift, and keep the Assurance Pack up to date as you ship.
