From rough system idea
to structured model.

Cairn is an AI engineering workspace that turns ideas into inspectable, structured system models — not chat transcripts.

Cairn
Autonomous Delivery Rover Power Subsystem Battery Pack|
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OverviewBriefRequirementsArchitectureBehaviorVerificationVisuals
Battery PackASM-BATTPDUASM-PDUCharging I/FASM-CHRGMotor ECUASM-ECUHub MotorsASM-HUBCAN BUS · 4 signalsDC BUS · 400 V nominal
Model loaded24 nodes18 reqs7 interfaces2 visuals
24System nodes
18Requirements
7Interfaces
6Lenses
Product

See what a real engineering session looks like.

Start with a rough concept. AI asks focused clarifying questions and builds a refined system description.

Cairn
New Project AI Interview — Round 1
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Round 1 of 2Question 3 of 5

What detection modalities are you envisioning for fire sensing?

Sensor selection drives drone payload weight, power consumption, data processing requirements, and cost per unit.

Thermal imaging only
Multi-modal (thermal + gas sensors + visual)
Visual spectrum with AI analysis
✓ Coverage area → Small reserve (1–50 km²)
✓ Autonomy model → Fully autonomous
Refined descriptionConfidence 68%

The Forest Fire Early Detection Swarm System is a fully autonomous multi-drone surveillance network designed to provide continuous aerial coverage of a small forested reserve (1–50 km²) during high fire-risk daytime hours.

The system uses multi-modal sensors including thermal/infrared imaging, gas sensors (CO/CO₂), and visible-spectrum cameras for early fire detection.

Additional details will be refined in the next round of questions...

68%
Workflow

Four steps from idea to model.

01

Describe

Start with a rough concept or engineering brief.

02

Decompose

AI interview refines it into a navigable system tree.

03

Inspect

Move between six lenses without losing the model.

04

Refine

AI proposes; the model stays yours to edit.

The model stays visible

What gets created is an explicit system model you can inspect, navigate, and continue refining — not a transcript dressed up as a product.

Built for serious work

Dense system trees, diagrams, inspectors, and simulation output belong on a real canvas. Designed for depth, not compromise.

Immediate and self-contained

Direct, fast, and close to the model. Everything runs locally today, with cloud persistence on the roadmap.

Thesis

The model is the artifact,
not the conversation.

AI should contribute structure to a persistent, inspectable engineering model — not generate disposable text that vanishes when the chat window closes. Every node, interface, and requirement in Cairn is explicit, traceable, and yours.

Roadmap

Where Cairn is headed

Now
Working prototype

Full modeling, AI decomposition, six lenses, changeset review.

Next
Cloud persistence

Save, return, continue across sessions.

Later
Collaboration

Shared workspaces and multi-user modeling.

Vision
Production platform

Simulation, verification, export, full lifecycle.

An AI systems design workbench for turning rough ideas into structured models.