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Your AI models ship fast.
Your auditors move slow.

Sentinel is ML governance for financial services — model versioning, approval workflows, and audit trails that satisfy regulators without slowing down your team.

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The gap between your ML team and your compliance team is costing you.

Your data scientists ship models. Your auditors ask for lineage. Nobody has a single source of truth.
Champion-challenger experiments run in notebooks. Promotion decisions live in Slack threads.
When regulators ask "which model made this decision, and why?" — you scramble.

What Sentinel does.

Model Governance

Version control for models, not just code
Approval workflows with promotion gates
Champion-challenger with documented metrics

Audit Trails

Full data lineage from source to prediction
Immutable logs of versions and decisions
Reproducibility at any point in time

Compliance Reporting

Automated documentation for regulators
Pre-built templates (SR 11-7, MRM)
Export-ready audit packages

Go deeper.

Our whitepaper explains the architectural patterns behind compliant ML deployment — why traditional CI/CD fails in regulated environments and how to fix it.

Read the Whitepaper →

Built for teams that can't afford to get this wrong.

ML Platform teams deploying models in production
Risk & Compliance officers responsible for AI governance
Engineering leaders writing the playbook for responsible AI

Let's talk about what governance looks like for your team.

We've built ML platforms in regulated enterprise. We know what auditors actually ask for.