← Selected work
C-01 Mining & resources

Mining intelligence platform

An integrated, map-first system that pulls scattered claims, corporate, geological, and market data into one place you can actually query.

Real project · client withheld · outcomes discussed under NDA

  1. 01 One spatial source of truth
  2. 02 Scheduled ingestion
  3. 03 Satellite mineral mapping
  4. 04 AI-assisted extraction
1730 / C-01 / Data backbone Build path / 4 stages PostGIS

Anyone tracking mineral exploration works from sources that never sit together — public claims and tenure registries, corporate filings, deposit databases, satellite imagery, and market feeds, each in its own format and on its own update cycle.

The problem

Keeping a current picture of what is staked, by whom, and what it might be worth meant stitching those sources together by hand, over and over. The same facts lived in several places, went stale quickly, and were hard to reconcile against what was actually on the map.

What we did

  1. 01
    One spatial source of truth

    A PostGIS model that holds claims, companies, projects, and deposits together, so tenure lines up with geology and corporate ownership instead of living in separate spreadsheets.

  2. 02
    Scheduled ingestion

    Pipelines that keep claims, tenure, corporate, and market data current on a schedule, rather than someone re-pulling and re-pasting it.

  3. 03
    Satellite mineral mapping

    Remote-sensing-derived mineral indicators layered onto the same map as the tenure and deposit data, so the geology sits beside who owns the ground.

  4. 04
    AI-assisted extraction

    Structured facts pulled out of long technical documents and filings by an LLM step — with human review before anything is written to the database.

Relevance

Where this pattern applies.

  • Claims, ownership, geology, filings, and market data are still being reconciled by hand.
  • A map is the natural way to inspect the system, but the data underneath is not yet current or trustworthy.
How we would start

A comparable engagement usually starts with a short, paid data diagnostic — inventorying what data you have and where it lives — then a PostGIS-backed model and the first ingestion pipelines, with map and search layered on once the backbone is trustworthy.