Geospatial Solutions

Solar digital twin pilots — built on an inspectable facility schema

Turn solar imagery into a site model your team can trust.

Start with a sample site. Lock the asset schema and QA rules. Extract panels, inverters, combiner boxes, cable runs, and exceptions into a reviewable geospatial twin — every feature tied to an ID, an attribute set, and a validation state.

Book a solar twin pilot

For existing imagery or draft asset layers outside this solar workflow, see geospatial annotation and GIS QA services.

Open the live editor

Scoped pilot

timing confirmed after source and acceptance review

185+ fields

managed attributes across the solar asset schema

QA trail

exceptions, confidence, and reviewer notes kept visible

Sample first

Test one representative site or area before scaling the twin across the portfolio.

Schema & QA locked

Classes, attributes, geometry, confidence, and acceptance rules are fixed before production.

Inspectable handoff

You leave with a site model, a QA log, and a scoped quote for full-site production.

The solar asset schema

Every twin is built on a real, remappable data model.

The digital twin is not a pretty model — it is a structured asset inventory. Browse the demonstration schema below: pick a category, choose a feature class, and see the exact attributes, geometry, and value sources we capture. Field names and domains remap to your existing GIS or CMMS naming conventions.

6
Asset categories
22
Feature classes
185+
Managed fields
3
Geometry types

Site & Field

Boundaries, fencing, gates, and access drives that frame the site.

PV Array

Panels, racking, and tracker hardware that generate the power.

Collection & Wiring

Combiner boxes, cable, conduit, and trench routing the current.

Power Conversion

Inverters, transformers, and power stations stepping power up.

Monitoring & Data

Weather stations and data acquisition feeding performance models.

Protection & Switching

Switchgear and disconnects that isolate and protect circuits.

PV Panel

PV Array · Polygon feature

12

fields

FieldSourceEditable
Location
location
Panel location
user input
String Number
string_number
String the panel belongs to
template default
Combiner Box
combiner_box_id
Associated combiner box identifier
template default
Date Cleaned
date_cleaned
Last cleaning date
user input
Owner Funded
owner_funded
Whether owner-funded
user input
SHAPE_Length
shape_length
Panel perimeter
calculated
SHAPE_Area
shape_area
Panel area
calculated
Install Status
install_status
Installation lifecycle
ProposedIn DesignApprovedInstalled+1
template default
Notes
notes
Free-text notes
user input
Identity fields (OBJECTID, GlobalID, FacilityID) are managed automatically.

Source: derived from a representative utility-scale solar facility schema. It is operational, not illustrative — and every field name, domain, and geometry type can be remapped to your conventions with no proprietary lock-in.

The Solar Utility Network Editor with feature attributes, validation queue, and GIS export panel.

The working environment

Where the schema becomes an editable, validated twin.

The same schema powers the Solar Utility Network Editor — a web-based workspace where panels, inverters, nodes, collection lines, switches, and transformers carry live attributes, connectivity, and validation state over satellite imagery.

  • Click any feature to inspect and edit its attribute record
  • Run validation to surface high-priority and informational issues
  • Trace connectivity from a node through the collection network
  • Export clean layers to GIS, CAD, or a maintenance report
Open the live editor demo

Pilot workflow

Sample data first, schema lock, QA review, then a production quote.

Great drone hardware hands you 10,000+ images. The value is in turning that capture into a structured, validated twin. Here is how the pilot runs.

01

Send sample site data

Share drone imagery, orthomosaic tiles, as-built CAD, asset lists, or a small representative site area.

02

Lock schema & QA rules

Confirm feature classes, IDs, attributes, geometry types, acceptance criteria, review stages, and output format.

03

Extract & build the twin

Map assets, attach attributes, flag uncertain cases, and reconcile imagery against available records.

04

Deliver the pilot packet

Review the sample twin, QA log, exception list, and a scoped quote for full-site production.

Pilot output

A solar twin packet you can inspect before scale-up.

The first deliverable proves model quality on real data and defines what it takes to scale across a site or portfolio.

Panel, inverter, and access layers tied to asset IDs

QA log with exceptions, uncertainty, and reviewer notes

Pilot quote for full-site digital twin production

Pilot package

Test quality on a real solar sample before scaling the site model.

Bring one representative site or asset area. Leave with the schema, the QA approach, and your first production scope.

Book solar twin pilot

Implementation stack

Technologies We Work With

We choose the stack around the job: browser maps for decision surfaces, spatial databases for reliable data, Python and GIS libraries for analysis, and annotation tools when imagery needs reviewer-ready labels.

QGIS

GIS Software

ESRI ArcGIS

GIS Platform

PostgreSQL

Database

PostGIS

Spatial Database

AWS

Cloud Platform

Google Cloud

Cloud Platform

DuckDB

Analytics Database

OpenAI

AI Platform

Claude AI

AI Assistant

CVAT

Annotation Tool

Python

Programming

React

Frontend

Node.js

Backend

Docker

Containerization

Kubernetes

Orchestration

Azure

Cloud Platform

TensorFlow

Machine Learning

Pandas

Data Analysis

NumPy

Scientific Computing

Jupyter

Data Science

Git

Version Control

Linux

Operating System

Ubuntu

Operating System

Mapbox

Mapping Platform

Leaflet

Web Mapping

Fastapi

API Framework

GeoPandas

Geospatial Analysis

GDAL

Geospatial Library