Imagery question-answering
Ask plain-English questions of aerial, drone, satellite, or inspection imagery and get answers with confidence and caveats.
GIS automation, GeoAI, imagery QA, and repeatable spatial reports
Turn one-off GIS work into a repeatable decision system.
We start with the decision your team keeps making by hand, show you a working example of the result, then build the smallest reusable pipeline, report, dashboard, or review queue that takes the manual work out of it.
01
GeoAI first
Spatial Need, Foot Traffic, and naipai show the decision before the custom build.
02
Real data sources
Census, Overture, Foursquare, FHWA/NBI, SDOT sign records, imagery, and GIS exports.
03
Reusable handoff
Runbook, QA states, source notes, and export formats are part of the deliverable.
See it working
Try a working example before we scope yours.
Live tools built with the same methods we use in client automation: maps, reports, imagery answers, source notes, and export paths you can inspect today.
Spatial Need AnalyzerFind underserved areas by scoring population density, amenity proximity, and coverage gaps on a hex grid.Data proof: Census block-group context, place listings, saved scenarios, shareable analysis viewsBuilt for: Cities, planners, public health, retail expansionOpen GeoAI need proof
Foot Traffic Popularity ScoreRank businesses and corridors around an address before choosing a site, tenant, or expansion area.Data proof: Foursquare popularity, Overture Places, 400m / 800m / custom trade-area lensesBuilt for: CRE, franchise, retail, investorsOpen foot-traffic proof
naipai imagery chatAsk plain-English questions of aerial, drone, satellite, or inspection imagery and turn answers into notes.Data proof: Vision-language review, visible evidence, confidence and caveat handling, export-ready answer patternsBuilt for: Imagery analysts, inspections, emergency responseAsk imagery questionsWhat gets automated
A practical menu for GIS work that keeps coming back.
The right first phase is usually not a giant platform. It is one repeatable workflow with clear inputs, validation checks, output formats, and human review points.
Scope my workflowLocation report generation
Turn an address, parcel list, or corridor into repeatable reports with maps, evidence tables, assumptions, and exports.
Annotation QA pipelines
Move from raw imagery to reviewed labels, geolocation fixes, QA logs, and final GeoJSON or customer-schema delivery.
Route and access checks
Package bridge, clearance, access, staging, and field constraints into a reviewable route or arrival workflow.
Field data to dashboard
Standardize Survey123, KoboToolbox, ODK, spreadsheets, shapefiles, and API pulls into one operational view.
Recurring map production
Automate joins, buffers, overlays, styling, exports, report packets, and reviewer states so maps stop being rebuilt by hand.
How we engage
From first example to a workflow you own.
Each step gives you something to judge before the next: the question, a working example, the smallest automated slice, then the repeatable system.
01
Name the decision that repeats
What decision repeats: where to open, what changed in imagery, which records need QA, what route is acceptable, or which assets need review?
02
Start with a proof route
We point you to the closest live example (Spatial Need, Foot Traffic, naipai, annotation QA, or route intelligence) so you can see the shape of the result first.
03
Scope the first automated slice
Define inputs, assumptions, data source notes, validation checks, output format, and the first production deliverable.
04
Ship the repeatable workflow
Deliver the pipeline, dashboard, report, export, or review queue with a runbook and clear human review points.
Real data and outputs
See exactly what goes in and what comes out.
What comes in, what gets checked, and what comes out, for the kinds of automation we build. Real operational data, not generic AI claims.
GeoAI need scoring
Census context, place listings, amenity coverage, hex-grid scoring, saved/shared analyses
Foot traffic reporting
Foursquare popularity, Overture Places, radius-based trade areas, ranked nearby places
Imagery chat
Aerial, drone, satellite, inspection, or custom imagery with answer confidence and caveats
Transportation review
FHWA/NBI bridge records, route alternatives, access constraints, explicit no-status states
Annotation delivery
Street-level imagery, QA decisions, GeoJSON, COCO, KITTI, Mapillary, or customer schema
Annotation handoff
When the automation needs labeled data
Automation often creates a review queue that still needs human-in-the-loop extraction, QA, and GIS delivery. These demos show how we handle that part. Review the commercial annotation and GIS QA scope.
Geospatial data annotationSource imagery, map-linked asset records, QA decisions, and export-ready delivery.Open demo
Striping and markingRoadway frames, pavement marking QA, and production-ready GeoJSON sample output.Open demo
ROW asset QAHydrants, manholes, catch basins, guardrails, poles, cabinets, shelters, and curb ramps.Open demo
Infrastructure extractionStreet-level imagery to classified infrastructure assets with QA records and deliverables.Open demo
Traffic sign GIS deliveryReal sign records, review status, lineage, map-linked imagery, and GIS-ready export flow.Open demoStart with the next usable decision
Bring the repetitive GIS work. Leave with the first automation build path.
We will map the inputs, choose the closest proof route, define the first deliverable, and separate what the system can automate from what still needs human review.