AuthZed Blog

Next week, RSAC and KubeCon happen at the same time. While the two shows have very different core audiences, the overlap in topic this year is striking—especially around authorization as a key driver of AI and agentic security.

AI agents decide what to access, which tools to call, and what actions to take—autonomously, at volume, and in ways most permission systems weren't designed to handle. AuthZed is the authorization platform built to close that gap.

We're announcing langchain-spicedb, a new library that brings SpiceDB's relationship-based access control into LangChain and LangGraph workflows. Build RAG pipelines that respect what users are allowed to see with post-retrieval filtering, LangGraph auth nodes, and agent permission tools.

Policy engines promise flexible authorization, but they struggle with the ambient context and relationship-driven decisions that AI systems require. Learn why Relationship-Based Access Control (ReBAC) is the better approach for securing AI agents and RAG pipelines.

Policy engines are being pitched as the solution for AI agent authorization, but they fall short in dynamic, relationship-heavy environments. Jake Moshenko breaks down why relationship-based access control is a better fit as we start treating AI agents more like people than scripts.

Introducing the SpiceDB Foreign Data Wrapper (FDW) for PostgreSQL — a new experimental way to bring real-time authorization context from SpiceDB into Postgres queries, without duplicating data or embedding authorization logic where it doesn't belong.

The SpiceDB query planner project explains the architecture on how we're improving the performance of every permission check.

The AuthZed Cloud Starter Program provides a $700 credit to try out AuthZed Cloud and see the value of scalable authorization infrastructure.

While many companies push return-to-office, AuthZed stays remote-first. Our secret is regular off-sites where bonding and business coincide. When we prioritize being human together, we return with more empathy, better communication, and renewed drive to solve hard problems.

MCP, A2A, and ACP standardize how AI agents communicate, but none adequately address authorization. This post analyzes specific vulnerabilities in token granularity, revocation propagation, and delegation chains, and outlines requirements for secure agent infrastructure.

Five years in, our mission remains the same, fixing access control. 2025 was about making our authorization infrastructure available to more teams in more ways.

MCP standardizes how AI agents connect to tools and data. What it doesn't do is secure them. The spec addresses authentication plumbing but leaves authorization decisions to implementers. So how do you build with MCP without recreating the mistakes behind 2025's breach timeline? It starts with understanding where the protocol ends and your responsibility begins.

AI fundamentally changes the interface, but not the fundamentals of security. Here's a timeline of security breaches in MCP Servers from the recent past.

Learn how to build a complete retrieval-augmented generation pipeline with multi-tenant authorization using Motia's event-driven framework, OpenAI embeddings, Pinecone vector search, SpiceDB permissions, and natural language querying.

AuthZed now supports Terraform and OpenTofu. You can manage service accounts, API tokens, roles, and permission system configuration as code, just like your other infrastructure. Define resources declaratively, version them in git, and automate deployments across environments without manual configuration steps.

Should your company rebrand as an AI company? We decided not to. AI companies attract outsized funding and partnership dollars. Yet rebranding means trading established brand value and customer mindshare for alignment with today's hottest trend. We stayed brand-neutral because our authorization solution serves both AI and non-AI companies alike. Limiting ourselves to AI-only would be a disservice to our broader mission and the diverse customers who depend on us.