AI + Proprietary Data

This category is about companies sitting on genuinely proprietary data — not protected by legal contract, but generated by the company's own operations and impossible to replicate by training on the public internet. Sensor data from industrial deployments. Claims history from insurance operations. Transaction patterns from financial infrastructure. Operational intelligence earned from thousands of real-world agent deployments.

The loop works because proprietary data feeds the harness, the harness makes the agents better, and better agents generate more proprietary data. The network effects get powerful when multiple nodes in a supply chain — supplier, operator, buyer, regulator — all run agents through a shared platform. The platform accumulates intelligence across the chain, not just within one customer.

That cross-node graph is structurally exclusive: no single participant could build it, no horizontal player goes deep enough to earn it, and switching means losing access to everyone else's data, not just your own. The companies building these platforms aren't collecting intelligence within a customer — they're building the intelligence graph of an entire vertical supply chain. The switching cost isn't your data walking out the door. It's everyone else's data walking out the door.