Train on your data. Leak none of it.
Every dataset feeding training, fine-tuning, and RAG — classified, redacted, and provenance-tracked before a model ever sees it.
Models memorize what you feed them.
The data pipeline is now part of the attack surface — and the mistakes are permanent.
Training data is forever
Once PII is in the weights, no patch removes it. The only safe moment to catch it is before training starts.
RAG is a live wire
Retrieval reads production data at query time. One over-permissioned index leaks a little, every day.
Provenance is the audit
When regulators ask what trained the model, "we believe it was clean" doesn't hold. Signed lineage does.
A gate before the GPU.
Classify at ingest
Every record labeled before it enters the pipeline — restricted fields flagged with the policy that governs them.
Data Classification →Redact, don't reject
Masking and tokenization keep datasets statistically useful without the risk — and the same guardrails cover RAG at query time.
MCP & AI Data Protection →Sign the lineage
Every release carries signed provenance your auditors — and your SOC — can replay end to end.
Autonomous SOC Analyst →Clean data in. Safe models out.
One gate covers training, fine-tuning, and RAG — provenance included.