Custom Solutions for Unique Challenges
If you need it, we'll build it
Overview
Specialized analyses, unique data pipelines, or entirely new geospatial platforms. Experience across renewable energy, real estate, environmental consulting, government, and more. Solutions that are robust, scalable, and maintainable for the long term.
How It Works: Visual Breakdown
See the complete automation workflow with diagrams and code examples
System Architecture
End-to-end custom solution development with MCP solution architect, YOLOv8 computer vision, PostGIS spatial analysis, and automated work order generation for rail inspection.
⚙️Key Components
AI agent analyzing requirements and designing optimal system architecture
Computer vision model detecting cracks, corrosion, and misalignment
Geo-referencing detected defects to precise rail network locations
ML model classifying defects as low, medium, high, or critical
Storing defect locations with rail network topology
Real-time visualization of defects sorted by severity and location
Generating repair tasks with location, priority, and photos
Visual Examples
See the solution in action with real dashboard examples and visual comparisons
Key Features:
Key Features:
💡Note: The dashboard screenshots above are placeholders. Actual screenshots will be added after finalizing native in-app dashboards or capturing real application screenshots. Image paths are specified for easy integration.
Automated MCP Agent Workflow
Powered by n8n, Make.com, and Model Context Protocol agents
Bespoke client request submitted
“Given these requirements for a custom geospatial solution: [Client needs real-time wildfire risk monitoring for 500 properties across California, integrating satellite imagery (MODIS), weather forecasts (NOAA), historical fire perimeters (CAL FIRE), and property boundaries. Needs automated daily risk scores, email alerts for high-risk properties, and interactive dashboard.] Design a custom workflow: suggest n8n architecture (trigger: daily 6 AM cron, data nodes: NASA FIRMS API for active fires, NOAA weather, CAL FIRE perimeters, PostGIS for buffers and risk scoring), recommend tech stack (n8n, PostGIS, Mapbox, Plotly, SendGrid), outline implementation steps (1. Set up data ingestion, 2. Build risk scoring algorithm, 3. Create dashboard, 4. Configure alerts), and estimate timeline (4-6 weeks) and cost ($25K-$35K).”
- Custom geospatial solution (fully tailored)
- Documentation (architecture, API, user guides)
- Training for end users and admins
- Source code (optional, per agreement)
- Maintenance and support plan
- Post-launch monitoring (30-90 days)
Key Features
Fully customized to your requirements
Scalable architecture (cloud or on-premises)
Integration with existing systems
Modern tech stack (Next.js, React, PostGIS, etc.)
Comprehensive documentation
User training and admin training
Post-launch support (30-90 days included)
Source code delivery (optional)
Technology Stack
API Integrations
Real-World Results
Challenge
Needed custom pipeline for processing 10K+ drone images per week (wetland delineation projects). Manual workflow: 40 hours/week for QA, georeferencing, classification, vectorization, and report generation. Client required automated pipeline with 95% accuracy and 24-hour turnaround.
Our Solution
Custom n8n workflow with 100+ nodes: file upload triggers workflow, MCP agent analyzes image quality and suggests processing parameters, GDAL georeferencing and orthorectification, Azure Computer Vision for wetland classification (trained custom model), PostGIS vectorization and topology cleaning, automated QA (comparing to ground truth samples), PDF report generation with maps and statistics, upload to client SharePoint, email notification. End-to-end processing: 2 hours (unattended).
Results Achieved
Flexible Pricing Options
Choose the plan that fits your needs
Test the solution with a limited scope project to validate ROI before full deployment.
Get StartedFull production deployment with hosting, monitoring, and ongoing updates included.
Schedule DemoWhite-label solutions, multi-tenant deployments, SLA guarantees, and dedicated support.
Contact SalesFrequently Asked Questions
Common questions about our GIS automation solutions
Still have questions?
Our GIS automation experts are here to help. Schedule a free consultation to discuss your specific needs.
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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