What We're Building

Frontier models now score above 170 on IQ tests. Reasoning isn’t the bottleneck. Context is.

The context layer sits between an enterprise’s siloed data and the agents that need to act on it. Stuff the context window and you trade quality for cost and latency. Use naive RAG and retrieval breaks the moment the question gets interesting. This gates most enterprise AI deployments we’ve seen, across private capital, professional services, edtech, and industrial data.

60x solves this. We built AI Brain, a knowledge graph platform engineered backwards from the agentic retrieval problem. Primary entity consolidation, chunk‑level provenance, scheduled enrichment, Cypher over Apache AGE. Agents retrieve what they need and the surrounding context, no bloat, no hope‑and‑pray.

We run a Palantir model for workflows. The platform sits at the centre. Forward‑deployed engineers wrap it around enterprise workflows we’ve template...