Public-sector and postal systems move a nation on top of enormous, messy, mission-critical data. We handle that layer — acquisition, structure, and modern AI — and bring it into the present. Cleanly. Consent-first.
We're a small, senior team that handles big data problems — the kind that stall inside legacy systems. We don't sell seats or shelfware. We handle the work.
We handle large-scale data acquisition from open records, public feeds, and operational streams — millions of entities, kept current. Finding the signal in the volume is the whole job, and it's the one we do best.
We handle the ugly middle: messy, decades-old, mission-critical records turned into typed, cited, query-ready intelligence that a modern system — or a modern model — can actually use.
Moving things across a country is a data problem before it's a physical one. We handle the awareness layer — entity maps, flow signals, where the friction is — built for the scale a national operation runs at.
We handle putting modern AI on top of federal-grade data — not a demo, a layer that answers, summarizes, and surfaces what matters. The models are the easy part; the clean data underneath is what we bring.
The Postal Service moves a nation every day. We handle the intelligence layer that helps a system like that see itself clearly — and step into modern AI without losing what makes it trusted.
That's the work we do: take enormous public data, make it clean and current, and put a modern layer on top — the honest way, with consent and compliance built in from the first row.
Senior people, no bloat. Big-league data problems handled by a crew that actually knows the pipes — not an army of billable hours.
Every source tracked, every touch logged, nothing taken it shouldn't be. Clean data isn't a feature here — it's the foundation.
What we handle at pilot scale, we handle at national scale. The architecture doesn't flinch when the problem gets big.
Tell us what you're moving and where it's stuck. We'll tell you straight whether we can handle it — and how we'd start small.
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