Gateco - Permission-Aware Retrieval for AI

Permission-aware retrieval for enterprise AI

AI copilots and RAG pipelines have unlocked your organization's knowledge, but vector databases don't understand who is asking. A single semantic search can return documents an employee was never cleared to see. Gateco closes that gap.

Gateco is the security middleware between your AI agents and your organizational knowledge. It enforces deny-by-default access policies on every retrieval, using the identity you already trust, so an internal copilot surfaces only what each user is authorized to see.

Works with your stack

• 12 vector databases, no re-ingestion: Azure AI Search, pgvector, Pinecone, Qdrant, Weaviate, Milvus, Chroma, OpenSearch, Supabase, Neon, and Google Vertex AI (Vector Search and Search).
• Identity from your IdP: Microsoft Entra ID, Okta, AWS IAM Identity Center, and Google Cloud Identity, with SCIM provisioning.
• Audit trail: every retrieval decision is logged with its full policy evaluation, so you can prove who accessed what through AI.

How it works

• Deny-by-default retrieval: every query is checked against policy before results are returned. No match, no data.
• RBAC, ABAC, and ReBAC policies: gate access by role, attribute, or relationship, and combine them in one policy set.
• Data classification: label sensitive content and cap what an assistant can return at a classification ceiling.
• Grounded Answers: cited answers synthesized only from policy-allowed content, never from denied documents.
• SDKs, CLI, and MCP server: add permission-aware retrieval in a few lines of Python or TypeScript.

Who it is for

Engineering and security teams building internal copilots, customer-facing assistants, and agentic workflows on regulated or sensitive data across financial services, healthcare, legal, and beyond.

Start free, then scale from Team to Enterprise with SSO, SIEM streaming, and dedicated support. Contact us to see Gateco applied to your Azure AI stack.