Applied AI · Security
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Custos
Private AI over internal documents, with retrieval-time authorization, cited answers, and human approval before tools can create real-world effects.
The hard decision
Restricted documents are removed inside the vector query. They never enter the candidate set, context window, answer, or citation.
PythonFastAPIQdrantAWSTerraform
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Engineering evidence
A documented suite of 61 adversarial evals covers eight threat classes, alongside automated application tests. The permission filter runs inside the vector query, so a restricted document is never a candidate for the answer. Qdrant and pgvector backends exercise the same contract. Tools with external effects require explicit human approval. The public demo uses simulated access roles and bounded usage; production identity must come from authenticated users.
