Scalable AI Governance Platform for Cross-Team AI Lifecycle Management

One policy framework, many teams

• A single governance framework applies across departments, so onboarding a new team doesn't mean rebuilding policy from scratch a new department inherits the model registry, access rules and quota policies that already exist.
• Each department can move through the lifecycle at its own pace, while staying under the same central rules.

Every stage of the lifecycle, covered

• Approve new models are reviewed and approved centrally before any team gets access a model that isn't enabled in the admin model registry simply isn't available to anyone.
• Roll out approved models are made available to specific teams based on role and data sensitivity. Employees request access to additional models in-app, and admins approve or reject from the console no tickets or email chains.
• Monitor usage, spend, and risk are tracked continuously once a model is live: every request is metered with token counts and computed cost per user and department, hard usage quotas are enforced before a request runs, and (with the CrowdStrike AIDR integration) guard events stream to your SOC's SIEM.
• Deprecate outdated or risky models are retired cleanly, with access revoked across every team at once. Conversation history and audit records are preserved in your account even after a model is retired.

Why this matters as adoption grows

Governance that only works for one team doesn't survive contact with real adoption. As more departments start using AI, a platform that requires a fresh setup for each one becomes a bottleneck rather than a safeguard. PixSpace is built so growth in usage doesn't mean growth in governance overhead one packaged deployment in your own AWS account covers every team from day one.

Where this fits

Frequently asked questions