Adding Gateco to a LangChain or LlamaIndex RAG Pipeline
Gateco is not a RAG framework. It is the authorization layer you insert at the retrieval step of LangChain or LlamaIndex. Here is where it goes, and why.
11 posts
Gateco is not a RAG framework. It is the authorization layer you insert at the retrieval step of LangChain or LlamaIndex. Here is where it goes, and why.
Gateco now supports per-org OpenAI keys for Grounded Answers, encrypted with AES-256-GCM and per-tenant KMS binding. Here is how the credit model works.
Google has two retrieval products under the Vertex AI brand: Vector Search, a managed ANN index, and Vertex AI Search, Discovery Engine. When to use each.
The Gateco MCP server gives Claude Desktop, Cursor, and any MCP host policy-enforced access to your vector knowledge bases. Denied content never surfaces.
Gateco now supports 1-hop relationship-based access control: policies can check whether a principal owns or is assigned to a resource. How and when to use it.
A summary of everything that shipped this month: relationship-based access control, API key authentication, SDK v1.0, and our new Trust Center.
Gateco now integrates with Google Vertex AI Vector Search and Vertex AI Search, bringing deny-by-default retrieval, ABAC policies, and audit trails to GCP.
Azure AI Search gives you hybrid retrieval. Gateco decides who can see the results. Why enterprise RAG needs both, and how they compose.
A step-by-step guide to connecting your identity provider to Gateco for policy-enforced AI retrievals.
Gateco now supports four distinct retrieval modes. Here's when to reach for each one, and why hybrid might be your new default.
We're launching Gateco, the security middleware between AI agents and organizational knowledge: deny-by-default retrieval, 12 connectors, and audit trails.