Generative AI Data Controls Community Version

The Generative AI Data Controls Community Version solves this problem at its root. It enforces strict boundaries on what data enters, leaves, and persists inside AI workflows. This is not a theoretical safeguard. It’s real, operational, and designed to be run locally or in the cloud.

With the Community Version, you define rules that intercept data before it ever reaches the model. Identify PII. Mask secrets. Block unwanted payloads. All in real time. No manual review. No guessing. If the data fails your policies, it never goes through.

The controls integrate cleanly with modern pipelines. Deploy alongside your existing vector databases, APIs, or orchestration tools. The enforcement works across fine-tuned models, large language APIs, and internal inference endpoints. This keeps both training and runtime safe.

Audit logging gives you a full record of what was blocked, allowed, or transformed. That record feeds directly into compliance checks, internal reviews, and incident response. The result is a disciplined, automated shield around your generative AI operations.

Because it’s the Community Version, you get it open and ready to run. Test it. Modify it. Embed it into CI/CD. There’s no guesswork about what happens under the hood—every policy is plain to read and open for inspection.

Your models only work as well as the data you let them touch. Use the Generative AI Data Controls Community Version to keep that data clean, safe, and compliant from day one.

See it live in minutes at hoop.dev and take control of your AI data flow now.