Version it, govern it, trust it. The single source of truth for every AI model in production — tracked, approved, auditable, and under control.
A data scientist fine-tunes a variant. An engineer swaps a provider. A quick experiment ends up serving real traffic. Soon no one can say with confidence what's running where — or why.
Models multiply across teams and environments with no centralized visibility or accountability.
Regulators ask which model produced a decision. "We're not sure" is not an acceptable answer.
Untracked model changes cause silent failures, performance regressions, and production incidents.
models.ms is the registry and governance layer that tracks every model in production — its version, lineage, owner, and risk — so AI scales without becoming a black box.
Every deployed model and version in one catalog — searchable, tagged, and always current. No more spreadsheets or tribal knowledge.
Trace any model from its training data to its production endpoint. Know exactly what data shaped every decision your AI makes.
Know who owns, built, and approved each model. Define accountability before a regulator or incident forces the question.
Capture purpose, limitations, and risk classification alongside each entry. Every model tells its own story — completely.
Every control you need to keep AI production safe, compliant, and auditable — built into one platform.
Models must clear review before they go live. Configurable multi-stage gates with sign-off requirements and audit trails.
Automated screening for bias, safety, and compliance. Define rules once; enforce them everywhere, automatically.
Govern who may deploy, change, or retire a model. Fine-grained RBAC with full permission audit logs.
Automatic warnings when performance degrades or behavior shifts. Catch regressions before users do.
Revert to any known-good version the moment something breaks. One command, zero panic, full traceability.
Satisfy regulators and stakeholders with a complete, immutable history. Every action, logged and timestamped.
A clean, repeatable path from experiment to production — with governance baked in at every step.
Capture model version, lineage, owner, and risk profile in the central registry.
Route through approval workflows and automated policy checks before any deployment.
Move models through staging, canary, and production with a controlled, traceable path.
Watch for drift, anomalies, and performance shifts in real time with automated alerting.
Tie every production prediction back to a specific, governed model version — instantly.
models.ms fits where governance matters most.
Organizations running many models across teams and products gain a single authoritative inventory — with clear ownership and risk classification for every asset.
Finance, healthcare, and insurance teams that must explain and defend AI decisions meet regulatory demands with complete, timestamped audit trails.
Platform engineers standardizing deployment and rollback eliminate ad-hoc procedures with repeatable, governed promotion pipelines that work at scale.
Any team that has lost track of what models are actually in production can import existing assets and restore full visibility — without disrupting live systems.
Security and compliance aren't bolt-ons at models.ms. They're the foundation every feature is built on.
Independently audited security controls covering availability, confidentiality, and processing integrity.
Governance workflows and risk classification align with emerging regulatory requirements for high-risk AI systems.
Every API call authenticated and authorized. Fine-grained permissions with full access audit logging.
Tamper-evident, append-only records of every registry action. The full provenance chain, always preserved.
Deploy in your cloud or ours. Single-tenant options available for the most sensitive environments.
Enterprise-grade availability with redundant infrastructure and 24/7 operational monitoring.
Before models.ms, our model inventory lived in three different spreadsheets and one engineer's memory. Now we have a single registry that the whole organization trusts. Our last audit took hours instead of weeks.
The approval workflow alone eliminated an entire class of production incidents. We used to discover model swaps after they'd been running for days. Now nothing goes live without a paper trail.
Our regulator asked us to demonstrate model lineage for a specific decision from 18 months ago. We pulled the complete trace in under a minute. That's the kind of answer that builds trust.