Intento Labs connects AI to building data — 3D models, documents, building codes, energy simulations — and is training the first purpose-built AI model for BIM.
Complex IFC models require expensive desktop software. Most stakeholders — clients, PMs, site teams — can't access or query the data they need.
Converting architectural models to energy models (IFC → IDF) takes weeks of manual work. Running EnergyPlus requires specialized expertise most firms don't have.
EU mandates whole-life carbon assessments. LEED and BREEAM require energy modeling. Firms are scrambling — paying $10K–$50K per building for manual consultancy.
$9.3B in 2025, growing to $29.6B by 2035 (12.2% CAGR). AI integration is the next major wave.
$6.4B in 2025, growing at 12.3% CAGR. EU EPBD mandates driving explosive demand for automated compliance.
$5.8B → $49.6B by 2035 (16.4% CAGR). The fastest-growing segment in all of AEC technology.
A shared AI backbone that connects any data source — 3D models, documents, building codes, simulation engines — to intelligent outputs.
AI-powered BIM platform. Upload an IFC, ask in natural language, get answers. Our roadmap: query → 3D IFC model generation — describe a building in words, get a full BIM model back.
We build custom AI pipelines for AEC enterprises — connecting any data source (3D models, document archives, building codes, energy engines) to AI-powered workflows. First delivered: IFC → space boundaries → IDF → EnergyPlus → carbon reports.
A specialized consultant manually recreates the building geometry in energy modeling software, assigns materials and systems, configures EnergyPlus, iterates on errors. 4–6 weeks, $10K–$50K per building.
Upload your IFC. Our pipeline automatically injects space boundaries, converts geometry, runs EnergyPlus, and delivers a full energy + carbon report. Minutes, not weeks. 90% cost reduction.
"How many doors on floor 2?" — answered in seconds with structured data from the IFC model.
"Create a wall with a window" — AI writes ifcopenshell code, executes it, loads the IFC into the viewer.
Full 3D viewer with Three.js. No installs, no plugins. Works on tablet, laptop, any device.
Gemini, GPT, Claude — user picks the model. BYOK for enterprises that want to use their own keys.
Distance measurement, annotation pins, exploded view, model diffing — built for real AEC workflows.
OAuth (Google/GitHub/Microsoft), Stripe credit billing, Supabase RLS — production-grade from day one.
BIM intelligence + energy simulation in one AI-native platform, working with full IFC fidelity.
| Capability | Autodesk | Text/MCP Adapters | Energy Consultants | Intento Labs |
|---|---|---|---|---|
| Browser 3D Viewer | ✗ Desktop only | ✗ | ✗ | ✓ BIMind |
| AI Chat with BIM | ✗ | ~ Text only, lossy | ✗ | ✓ Native IFC geometry |
| Full spatial / geometry reasoning | ✗ | ✗ Lost in conversion | ✗ | ✓ Preserved |
| IFC → Energy Model | Partial (Insight) | ✗ | Manual, 4–6 wks | ✓ Automated |
| Carbon Calculation | ✗ | ✗ | ✓ $10K–50K | ✓ Automated |
| IFC Generation | ✗ | ✗ | ✗ | ✓ |
| Price | $2,500+/yr | Fragile integrations | $10K–50K/project | Pay-as-you-go |
Converting IFC to text or JSON strips all spatial and geometric relationships — the AI loses the ability to reason about 3D space. MCP/plugin adapters bolt AI onto desktop software APIs that weren't built for it: brittle, slow, no control over context window or geometry.
The energy simulation pipeline we delivered for NRC Canada was previously attempted by a university research group — and failed. Other client problems we're solving had large players either declining or quoting 5–10× our price. Domain depth is not replicable quickly.
High-volume, low-touch. Product-led growth with viral sharing of model links.
High ACV, consultative sales. Replaces $10K–$50K manual consulting per building.
Completed a custom B2B energy simulation pipeline for the National Research Council of Canada. IFC → IDF → EnergyPlus → carbon reporting. Now negotiating a larger ~$200K follow-on project.
Full-stack SaaS in production. 3D viewer, AI chat, model generation, OAuth, Stripe billing, multi-AI provider support — all live. Text-to-BIM (query → IFC) currently in beta.
Active conversations with multiple prospects across AEC and one client in the pharmaceutical space. Deep IFC/BIM domain expertise and proprietary LangGraph agents give us a compounding moat.
BIMind for design QA and client presentations. EnergyAI for early-stage energy compliance.
Automated energy modeling replaces weeks of manual IDF creation. Focus on design, not data entry.
On-site model queries. AI answers about any element — dimensions, materials, specifications.
10× their throughput. Run energy + carbon analysis on more buildings with automated pipeline.
Understand building performance without technical expertise. ESG reporting made simple.
Automated compliance checks. AI validates models against energy codes and carbon targets.
BIMind SaaS live. 3-phase B2B solution delivered for NRC Canada. Client already asked for an extension + a second larger project is underway. Text-to-BIM (query → IFC) currently in beta.
Full Text-to-BIM pipeline out of beta. Self-serve B2B portal. 10+ customers. Begin training data collection. Expand NRC engagement.
The first purpose-built AI model for BIM/IFC — trained on building data, codes, and spatial reasoning. Massive competitive moat.
Enterprise (SSO, on-prem). Plugin marketplace. Revit/ArchiCAD integration. International expansion. Licensing our model to other AEC tools.
LangChain + LangGraph agents with BIM-specific tools. Multi-provider (Gemini, GPT, Claude). Connects to any data source: 3D models, documents, building codes, simulation engines.
The first purpose-built AI model for BIM. Trained on IFC schemas, building data, spatial reasoning, and construction codes. Nobody else is doing this — we'd be first and likely only.
Modular pipeline connecting any source to AI outputs: IFC/BIM models, EnergyPlus simulations, PDF building codes, document archives, Revit APIs, point clouds.
Deep expertise at the intersection of construction technology and artificial intelligence.
PhD in Geomatics Engineering (York University). Research on BIM-based energy modeling and IFC-to-ML pipelines. Deep domain expertise in building data science and construction technology.
7+ years ML/AI engineering. Specializes in GenAI, NLP, and LLMs. Built production systems at scale across healthcare, enterprise NLP, and construction AI.
MIB (Queen's / Erasmus Rotterdam). Background in institutional investment management, capital markets, and supporting Canadian SMEs in scaling responsibly.
Consulted with industry experts in digital construction, digital twin technology, and AI/robotics in construction to validate product direction and market strategy.
SAFE · Pre-seed round
Live platform. B2B contract delivered for NRC Canada, extension requested + larger project underway. $15.7B addressable market.
Training the first purpose-built AI model for BIM — connecting 3D, documents, codes, and simulation.
The built environment is the last major industry without an AI-native toolkit. We're building it.