Inspectial

From site visit to structured GIS-ready data, done by AI.

Inspectors capture photos, video, voice notes and GPS on site. Inspectial's AI turns that evidence into evidence-linked observations: it finds and codes the defects and writes the structured inspection record. A qualified reviewer approves every finding, and the approved, GIS-ready data goes straight into your asset systems.

Capture in the field. AI structures the evidence. A human approves. Export.

Join the pilot See how it works

Pre-launch. Now onboarding a small group of drainage inspection teams.

Product preview: a web map of the Route 12 drainage project, with stacks of geotagged field photos pinned at each culvert site and a sidebar listing each site's review status.

The site visit is the quick part. The paperwork is not.

A single culvert visit comes back as a pile of loose evidence. Someone in the office then sorts it, matches it to the asset, codes each defect by hand, writes the report, and updates the GIS.

Field work and office work stay disconnected, and the condition data your asset system needs is the last thing to get done.

Photosabout 35
Video clipsinlet, barrel, outlet
Voice and text notesunstructured
GPS and the previous inspectionin separate places
Then, by handcoding, report writing, GIS updates

Open any site to see how its photos become a structured record.

An inspector in a hi-vis vest and hard hat crouches beside a concrete culvert and photographs its circular barrel opening with a phone. Water runs out over the invert onto a gravel apron.
CULVERT C-1042
49.1231, 16.4561 · drainage pack
Example record
BARREL AI suggested
deformation
none visible
IMG_4821
joints
unclear
IMG_4822
OUTLET Human verified
flow
clear
IMG_4821
headwall base
moss, staining
IMG_4821
APRON AI suggested
riprap
displaced (possible)
IMG_4821
evidenceIMG_4821 (photo), IMG_4822
confidence0.91
Illustrative example. The numbered boxes on the photo map to the observations in the record, and every value links back to the evidence it came from.

How it works

One workflow from the site visit to the asset system. AI does the coding; people make the call.

  1. Capture offline, with location

    The field app guides the inspector through the required evidence: photos, video, voice and notes. Each item is stamped with time, GPS and asset ID. No signal needed; it syncs later.

  2. AI structures the evidence

    Evidence is grouped by asset and component, and turned into bounded observations: defect type, severity, confidence, and the evidence each one came from.

  3. A reviewer approves

    An engineer checks each finding next to its photos, then approves, edits or rejects it. The record always shows what the AI suggested and what a person verified.

  4. Export to your systems

    Approved data goes out as GeoJSON, CSV, a PDF report or through the API, into the GIS and asset tools you already use.

AI creates the inspection record, not just the report

Keep your ArcGIS or asset system. We automate the inspection-coding layer in front of it, under rules you can trust.

Field app preview: a map of today's route with culvert markers by inspection status, working offline, with culvert C-1046 selected and ready to inspect.

Field app preview. In development, for iOS and Android.
Evidence first
Every observation references the photos, clips or notes behind it. A finding never exists only as an AI sentence.
A human approves
AI proposes; a qualified person decides. Inspectial is not an autonomous inspector, and only approved inspections become official records.
Location is first-class
Evidence, observations and assets carry coordinates, so the output drops onto a map without cleanup.
Offline-first
The full capture flow works in a ditch with no signal. Data syncs when the connection returns.
Structured data over documents
The dataset is the source of truth. Reports are generated from approved observations, never written straight from the media.
Configurable, not custom-built
A new inspection type is a template: evidence checklist, observation schema, AI rules and report format. Not a new app.

Who it's for

Anyone who captures photo or video evidence in the field and has to write it up afterwards. We're starting with drainage.

First focus

  • Drainage and culvert inspection contractorsYou already have crews, cameras and reporting workflows. Inspectial is designed to cut the time spent coding footage and writing reports.
  • Municipalities and counties with small GIS teamsGet condition data that lands in your GIS without someone re-keying it.
  • Road maintenance contractorsInspect long runs of structures along a route, with status and priority per asset.

Inspection packs

  • Culverts and drainagePilot
  • BridgesComing
  • Utility polesComing
  • RoofsComing
  • Construction QAComing

Outputs and integrations

Inspectial feeds the tools you already run. It doesn't ask you to move your asset data anywhere.

Formats

  • GeoJSONMVP
  • CSVMVP
  • PDFMVP
  • REST APIMVP
  • Excelplanned
  • Shapefileplanned
  • GeoPackageplanned

Works with

  • ArcGISplanned
  • QGISplanned
  • PostGISplanned
  • MapLibreplanned

MVP: available in the first release. Planned: on the roadmap, not yet built. Until native connectors ship, GeoJSON and CSV load directly into most GIS tools.

Join the pilot

We're onboarding a small number of drainage inspection teams for a pilot. Tell us what you inspect, roughly how many structures a year, and which GIS or asset system you report into.

Email us about the pilot

pilot@inspectial.com

  • Bring real inspections: photos, video and the reports you wrote from them.
  • We set up a drainage template that matches your existing condition codes.
  • You review the AI's structured output against your own findings.
  • Exports go to GeoJSON, CSV or PDF in the format you need.