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AI agent for survey data · private beta

Ask your maps anything.

Geo-CoWork is an AI agent for drone and GIS survey data. Drop in orthomosaics, shapefiles and GeoJSON, ask a question in plain language, and get an exact answer — counted, checked and drawn on the map.

Get early access See how it works
  • GeoTIFF · GeoJSON · Shapefile
  • Exact counts, drawn on the map
  • Cloud or on-prem
  • GeoTIFF / COG
  • GeoJSON
  • Shapefile
  • Orthomosaics
  • Multispectral bands
  • Feature counts
  • Attribute search
  • Map highlights
  • NDVI · SAVI · NDRE
  • CSV & GeoJSON export
  • Share links
  • Chat history

01How it works

The agent does the GIS work.

No plug-ins, no desktop software, no query language. You bring the survey; the agent does the rest.

  1. 01 · Ingest

    Drop in the survey

    Orthomosaics, GeoJSON and zipped shapefiles. Multi-gigabyte files upload straight to storage.

    .tif · .geojson · .zip

  2. 02 · Understand

    It learns your data

    Imagery is tiled, bands are identified and every feature is indexed, so the agent knows what each file holds.

    tiles · bands · schema

  3. 03 · Ask

    Ask like a colleague

    Type a question in plain language. The agent plans it, runs real queries on your data and checks the result.

    plan → query → check

  4. 04 · Act

    See it on the map

    The exact number, highlighted where it is. Export it, share the view or ask the next question.

    map · export · share

02Use cases

One agent. Every kind of site.

If your work produces orthomosaics and annotated features, you can ask questions about it.

  • Solar

    Every module in the plant checked for soiling, cracks and hotspots, then rolled up by string.

    Show every string with four or more hotspots.

    5 strings · 23 hotspots

  • Agriculture

    Plant counts, stand gaps and canopy health for each block, every flight.

    Where did the new saplings fail to take?

    312 gaps · 4 rows

  • Infrastructure

    Bridges, roads and rail lines inspected end to end, defect by defect.

    Rank the bridge spans by their longest crack.

    Span 7 · 4.2 m

  • Oil & gas

    Well pads, tank farms and right-of-way corridors, compared survey to survey.

    Which well pads have standing water?

    3 of 18 pads

  • Construction

    Site progress measured against the design, flight after flight.

    Which piles in zone B are still missing?

    14 of 220 piles

  • Spectral indices

    NDVI, SAVI, NDRE and more from multispectral orthos. The bands are detected for you.

    Which plot is the most stressed?

    Plot 7 · NDVI 0.31

03Grounded answers

Every number has a receipt.

Language models are good at understanding a question and bad at counting. So the model never counts: it plans the work, and your data gives the answer.

  • Counts, areas and lists come from real queries on your data, never from the model's memory.
  • Every step is shown: how it read the question, the query it ran and what came back.
  • When a question is ambiguous it says how it read it: “broken panels” → cracked + hotspot.
  • Your projects stay inside your organization's own workspace.
agent trace · one question
  1. askhow many panels in block B need cleaning?
  2. plancount soiled panels inside zone B
  3. toolcount_features(class="soiled", zone="B")
  4. sqlselect count(*) from features where class = 'soiled' and zone = 'B'
  5. rows412 rows · 9 strings · 41 ms
  6. checksum of the 9 string counts = 412 ✓
  7. answer412 panels across 9 strings need cleaning.

Private beta · onboarding now

Bring one survey. Ask it anything.

The private beta opens to a few teams at a time. Share a sample of your data and we'll walk you through answers on it, usually within 2 business days.

Get early access See pricing

A person replies, not a bot · admin@pramiq.in