Practice
AI Capabilities · Data, AI & Analytics
AI & Geospatial Intelligence
One platform.
Every obstacle.
A renewable-energy infrastructure developer was planning cable routes between turbines and substations in spreadsheets and static GIS files — across water bodies, villages, forests, rail, and road. Kansoft built an AI-powered geospatial platform that computes the shortest viable path, routing around every obstacle. Computed, not drafted.
86 turbines connected 8 obstacle categories KMZ geospatial export
The Client & Context
An infrastructure developer scaling renewable energy — faster than its planning tools could keep up.
The client is a leading infrastructure developer in the energy sector, focused on delivering scalable transmission solutions for large-scale renewable energy projects.
As renewable installations expanded, the work of planning cable infrastructure between turbines and substations grew more complex with every new site. Routes had to be drawn through terrain that included water bodies, villages, forests, and existing rail and road networks — while engineering teams balanced cable capacity, feeder limits, and cost variations across multiple cable types.
Spreadsheets and static GIS files weren't built for that kind of multi-variable optimization. The team needed a system that could think through the trade-offs at the pace the business needed to move.
Key Challenges
Five constraints the existing process couldn't reconcile.
Manual geometry, coupled cost-and-capacity trade-offs, fragmented tools — and terrain that crossed eight categories of obstacle.
01
Manual engineering complexity
Traditional route planning required significant manual intervention. Every new project meant rebuilding the same calculations, extending timelines and pulling senior engineers into work that wasn't strategic.
02
Cost & capacity constraints
Cable types, feeder capacities, and cost variations all needed to be optimized together — not as separate decisions. Getting one wrong propagated through the rest of the plan.
03
Lack of unified planning interface
Engineering inputs were fragmented across spreadsheets, static map files, and disconnected tools. There was no single surface where a planner could see the full picture and act on it.
04
Limited collaboration visibility
Stakeholders — reviewers, partners, approvers — needed interactive outputs they could explore. Static PDFs and CSV exports slowed the approvals cycle and made consensus harder to reach.
05 · Obstacle-rich terrain
Every route crossed a different set of physical and regulatory boundaries.
Cable paths had to account for eight distinct categories of obstacle, each with its own engineering and approval implications: water bodies, villages, residential zones, forest areas, industrial zones, hills, railways, and roads & highways. The combinatorial complexity was the real problem — not any single obstacle in isolation.
Our Approach
Four capabilities, designed to live inside a single planning workflow.
An AI-driven geospatial intelligence platform — optimization algorithms, terrain analytics, and engineering configurations under one interface, so planners work end-to-end without exporting to other tools.
AI · AGENTIC
AI Optimization Engine
Automated route calculations that take terrain and obstacle constraints as inputs and return the optimal cable path — without an engineer redrawing it by hand for every revision.
GEOSPATIAL
Geospatial Intelligence Layer
Map-based visualization and editing built directly into the workflow. Planners see terrain, obstacles, and the proposed route in one view — and edit them in place rather than across tools.
MODELING
Scenario Modeling Framework
Capacity, cable-type, and cost simulations that let the team compare alternatives side by side — moving the cost conversation upstream into engineering, where it has more leverage.
DELIVERY
Workflow Automation
Export and notification automation that closes the loop between planning and approval. KMZ outputs land where downstream tools expect them; reviewers get the interactive map link without a follow-up email.
Solution Delivered
What we built — the platform, in six modules.
From secure project access and structured data ingestion to the interactive map, the optimization engine, engineering controls, and automated export — every module designed to keep the planner inside one workflow.
Project Management & Secure Access
Authentication with controlled access, a centralized dashboard to manage multiple renewable projects from one place, and project-level segregation so teams only see what they own.
Structured Data Input Framework
Downloadable project templates that standardize uploads, CSV-based ingestion for turbines, substations, and geolocation data, and validation at upload — bad rows get flagged before they pollute a model run.
Interactive Obstacle Mapping
Visual representation of terrain obstacles — water, forests, villages, residential and industrial zones, hills, railways, and roads — on a single map surface, with editable obstacle layers that feed straight into the optimization engine with no re-export step.
AI-Powered Route Optimization
Automated processing of obstacle data into optimization inputs and intelligent calculation of optimal cable routes given terrain, capacity, and cost constraints — re-running in seconds when an input changes, no more half-day redraws.
Engineering Configuration Controls
Turbines-per-cable selection to model different aggregation strategies, inline substation and feeder capacity editing on the map, and cable types and cost adjustments that flow through to the optimization run.
Export & Notification Automation
KMZ outputs compatible with the geospatial tools the team already uses, automated emails bundling the interactive map link and final route attachments, and an audit trail of who saw which version — captured for compliance and review.
Platform Architecture
Technology Stack
Built on a stack chosen for geospatial scale and engineering precision.
Every choice maps to a constraint the platform had to satisfy — interactive maps, AI optimization, geospatial output formats, and reliable notifications across distributed teams.
Interactive GIS web app
Map-first interface with editable obstacle layers & route visualization
AI optimization engine
Custom service ingesting terrain & engineering constraints, returning optimized routes
MongoDB Cloud Cluster
Document storage for nested project, asset & geospatial data, managed for scale
Obstacle & route modules
Separate processing so ingestion and route computation scale independently
SMTP email automation
Reliable, auditable delivery for route notifications & approvals — no 3rd-party dependency
KMZ geospatial files
Industry-standard export — opens directly in the GIS tools downstream teams already use
Measured Outcomes
From drafted by hand to computed in seconds.
Five things changed between the spreadsheet-and-GIS process and the platform planners use today.
86
Turbines connected
Routed to substations in a single optimized plan
8
Obstacle categories
Physical & regulatory boundaries, routed around
Seconds
Re-run on change
No more half-day manual redraws
KMZ
GIS-ready export
Opens directly in downstream design tools
| Metric | Before | After |
|---|---|---|
| Route planning | Manual & spreadsheet-driven | AI-powered automation |
| Obstacle handling | Static analysis | Dynamic geospatial modeling |
| Cost visibility | Limited | Configurable simulations |
| Decision speed | Slow | Accelerated |
| Collaboration | Fragmented | Unified digital platform |
What Changed for the Business
Beyond the platform — four ways the work compounded.
AI took over the repetitive geometry. Engineers kept the judgment — and the cost conversation moved upstream where it has leverage.
Engineering efficiency
AI reduced the dependency on manual route calculations — freeing senior engineers from repetitive geometry work and putting their time on the decisions that actually need judgment.
Infrastructure accuracy
Obstacle-aware optimization improved feasibility upfront and reduced the rework that happens when constraints surface late in approvals.
Cost optimization
Scenario modeling moved cost into the engineering conversation rather than after it — enabling better cost-performance decisions before commitments harden.
Scalable planning model
The platform created a repeatable framework that scales to future renewable projects without rebuilding the planning approach for each one.
Engagement Snapshot
How the work was shaped.
Use Case
Cable route planning
Asset Scope
Turbines · Substations
Output
KMZ geospatial · custom platform
Why Kansoft
The capability mix this engagement required.
AI optimization, geospatial intelligence, and engineering workflow — in one platform, not three. Few teams ship all three in production.
Production AI optimization Deep expertise in AI-powered optimization systems — production AI, not pilot work that stalls at the demo.
Geospatial & engineering intelligence Strong capability in geospatial and engineering intelligence platforms, where the map is the interface, not an afterthought.
Energy & infrastructure digitalization Experience digitalizing energy and infrastructure workflows across global markets — domain, not just code.
One platform, not three Ability to combine AI, analytics, and operational workflows into a single platform — so planners never leave the workflow to get an answer.
Ready to build something like this?
If your infrastructure planning is still being done in spreadsheets, the next call is the one worth having.
We help energy, utilities, and infrastructure organizations build the AI and geospatial systems that turn complex engineering decisions into repeatable workflows. If that's where you're headed, let's talk.
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