Companies are quietly turning into networks of agents. The teams winning right now don't have better models — they have a place where every agent shares the same context, the same primitives, and the same memory of work in flight.
The Problem
Every AI-native team we talked to was running into the same pattern: more agents, more harnesses, more prompts, and the same docs and decisions copy-pasted into each one. Knowledge fragmented across tools. Long-horizon work fell apart at every handoff. New agents started from zero, every time.
CortexGraph started from a simple observation: the bottleneck in multi-agent work isn't intelligence — it's shared context. The harnesses don't talk. The memory systems are proprietary. Every new tool adds another silo. The companies furthest along are the ones treating context as infrastructure, not as prompt engineering.
So we built the layer underneath: one workspace per company, ingestion that captures knowledge once, primitives that match how the business actually thinks, and an MCP surface every agent can plug into. No SDK lock-in. No proprietary memory. Just a shared graph that humans and agents both operate on.
Our Core Belief
Agents are interchangeable. Context is not. Treat your context graph as infrastructure and the agents become plug & play.