Open permits
≥ $250K
cross-referenced against a 500K-profile bench
An AI that just answers needs a context window. An AI that acts — that decides, forecasts, and transacts — needs persistent, structured evidence to act against. Lakehouse ingests messy, real-world data and turns it into a queryable index a model can trust — and it gets sharper every time it's used.
Public records, live feeds, filings, documents — the raw, unstructured world.
Normalized, cross-referenced, and vectorized into evidence a model can query — with the trace of how it got there.
Agents forecast, decide, and transact against ground truth — not a guess from a context window.
It's an index that learns from you. Every query, every contract, every correction sharpens what it knows — so the system you use in month six is better than the one you started with, on your own data.
Every number traces back to the observation behind it. When a model acts on Lakehouse, the reasoning is auditable — which is the only way to trust software that spends money or makes decisions on its own.
Persistent, structured, auditable — the ground truth agents act against.