White paper

Train your OutSystems AI agents on O11 data without the risk

You want to build agents in the OutSystems Agent Workbench. They need rich, production-realistic O11 data to ground and test against. And your security policies won't let anything touch live production. That's the bind.

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Don't let bad data create bad AI

Fake or oversimplified test data starves your models of the real-world complexity they need. You get agents that look fine in a demo and fall apart in production, with hallucinations that cost you trust.

The usual choice is a bad one. Risk a breach by touching production, or ship agents trained on data that doesn't reflect reality. There's a third way, and it's what the white paper covers.

The blueprint for secure AI innovation

Fuel Your ODC AI Agents with Safe, Production-Realistic Data

A step-by-step strategy for creating fully anonymized, referentially-intact replicas of your O11 production data, so your agents learn from something real.

The secure data bridge

A repeatable method for moving O11 data into your ODC development and test environments, without exposing production.

AI grounding and RAG

Use high-fidelity data to ground your agents in reality and cut down the inaccurate outputs that kill trust.

Compliance by design

An anonymization framework built to meet GDPR, so you can move fast without the compliance fear.

Accelerated development

Give your teams data that mirrors production, and let them test and validate agents faster.

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