IntentoLabs

The AI Platform for the Built Environment

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.

IntentoLabs Overview

Intento Labs is a Toronto-based technology company developing artificial intelligence solutions for the architecture, engineering, and construction (AEC) industry. The company combines expertise in Building Information Modelling (BIM), spatial data science, machine learning, and software engineering to help organisations make better use of building information. Its focus is on making complex BIM and Industry Foundation Classes (IFC) data easier to access, analyse, validate, and apply throughout the building lifecycle.

Founded by Hamid Kiavarz and Pouya Hallaj Zavareh, Intento Labs brings together research experience in geomatics and building energy modelling with practical expertise in generative AI, natural language processing, and enterprise software development. This combination shapes the company’s approach: understanding the technical challenges faced by AEC professionals and developing AI tools that fit their workflows. Accuracy, reproducibility, sustainability, and collaboration guide its product development and client engagements.

The company’s flagship application, BIMind, enables users to interact with BIM/IFC models through natural-language conversations. By combining a BIM viewer with specialised AI agents, BIMind allows users to ask questions about building elements, explore model information, and analyse their projects within a visual environment. Its capabilities include querying, creating, and modifying IFC models, alongside workflows for model validation, construction scheduling, and cost estimation. The aim is to make building information more accessible while reducing the manual effort involved in extracting and interpreting model data.

Beyond BIMind, Intento Labs offers services across data engineering, BIM/IFC processing, 3D spatial analytics, digital twins, and compliance validation. Its data engineering capabilities cover the processing and integration of IFC files, point clouds, and sensor information. BIM workflows include data extraction, format conversion, model transformation, and validation. Spatial analytics services address geometric analysis, relationships between building elements, 3D visualisation, and clash detection, helping teams understand both individual components and the wider context of a building model.

For organisations working with project standards and information requirements, Intento Labs develops automated checking and reporting workflows. These include IFC validation, Information Delivery Specification (IDS) checks, and support for reviewing models against defined rules and requirements. Its digital twin solutions focus on connecting building models with operational information, including sensor data, to support performance monitoring and predictive analytics. These capabilities are relevant to engineering coordination, asset management, portfolio review, and construction planning.

Building energy analysis is another area of development. Intento Labs is developing EnergyAI, with an enterprise web application planned to support IFC-to-IDF conversion, energy simulation workflows, and carbon-related analysis. This work connects building information with energy modelling processes to help teams investigate building performance and potential improvements.

The company’s technical foundation combines open BIM technologies with graph-based data processing and AI infrastructure. Tools such as IfcOpenShell and web-ifc support IFC workflows, while Neo4j, LangGraph, and GraphRAG form part of its approach to connected data and AI orchestration. EnergyPlus and OpenStudio support its energy analysis work. Together, these technologies provide a foundation for connecting model geometry, properties, spatial relationships, and analytical processes.

Intento Labs also develops custom business solutions for organisations with specific integration, security, or workflow requirements. Delivery options include API-based integrations and on-premises deployments, with support for local language models where keeping project information within an organisation’s own environment is a priority.

Through collaboration from proof of concept to production, Intento Labs aims to help AEC organisations turn complex building data into practical tools for design, analysis, construction, and operations. To explore its products, discuss a project, or arrange a demonstration, visit https://www.intentolabs.io/.

Intento Labs is a Toronto-based technology company developing artificial intelligence solutions for the architecture, engineering, and construction (AEC) industry. The company combines expertise in Building Information Modelling (BIM), spatial data science, machine learning, and software engineering to help organisations make better use of building information. Its focus is on making complex BIM and Industry Foundation Classes (IFC) data easier to access, analyse, validate, and apply throughout the building lifecycle.

Founded by Hamid Kiavarz and Pouya Hallaj Zavareh, Intento Labs brings together research experience in geomatics and building energy modelling with practical expertise in generative AI, natural language processing, and enterprise software development. This combination shapes the company’s approach: understanding the technical challenges faced by AEC professionals and developing AI tools that fit their workflows. Accuracy, reproducibility, sustainability, and collaboration guide its product development and client engagements.

The company’s flagship application, BIMind, enables users to interact with BIM/IFC models through natural-language conversations. By combining a BIM viewer with specialised AI agents, BIMind allows users to ask questions about building elements, explore model information, and analyse their projects within a visual environment. Its capabilities include querying, creating, and modifying IFC models, alongside workflows for model validation, construction scheduling, and cost estimation. The aim is to make building information more accessible while reducing the manual effort involved in extracting and interpreting model data.

Beyond BIMind, Intento Labs offers services across data engineering, BIM/IFC processing, 3D spatial analytics, digital twins, and compliance validation. Its data engineering capabilities cover the processing and integration of IFC files, point clouds, and sensor information. BIM workflows include data extraction, format conversion, model transformation, and validation. Spatial analytics services address geometric analysis, relationships between building elements, 3D visualisation, and clash detection, helping teams understand both individual components and the wider context of a building model.

For organisations working with project standards and information requirements, Intento Labs develops automated checking and reporting workflows. These include IFC validation, Information Delivery Specification (IDS) checks, and support for reviewing models against defined rules and requirements. Its digital twin solutions focus on connecting building models with operational information, including sensor data, to support performance monitoring and predictive analytics. These capabilities are relevant to engineering coordination, asset management, portfolio review, and construction planning.

Building energy analysis is another area of development. Intento Labs is developing EnergyAI, with an enterprise web application planned to support IFC-to-IDF conversion, energy simulation workflows, and carbon-related analysis. This work connects building information with energy modelling processes to help teams investigate building performance and potential improvements.

The company’s technical foundation combines open BIM technologies with graph-based data processing and AI infrastructure. Tools such as IfcOpenShell and web-ifc support IFC workflows, while Neo4j, LangGraph, and GraphRAG form part of its approach to connected data and AI orchestration. EnergyPlus and OpenStudio support its energy analysis work. Together, these technologies provide a foundation for connecting model geometry, properties, spatial relationships, and analytical processes.

Intento Labs also develops custom business solutions for organisations with specific integration, security, or workflow requirements. Delivery options include API-based integrations and on-premises deployments, with support for local language models where keeping project information within an organisation’s own environment is a priority.

Through collaboration from proof of concept to production, Intento Labs aims to help AEC organisations turn complex building data into practical tools for design, analysis, construction, and operations. To explore its products, discuss a project, or arrange a demonstration, visit https://www.intentolabs.io/.

Specs

Headquarters
Canada
Firm Size
Small (1-50)
Specialties
Mixed UseResidentialCommercial/CorporateHospitalityTransportation/InfrastructureInterior DesignLandscape Architecture
Supported Lifecycle Phase
Planning and Programming (Pre-Design)Schematic Design (Conceptual Design)Design DevelopmentConstruction DocumentationBidding and Negotiation (Procurement)Construction PhaseOperation & Maintenance

Tools developed by IntentoLabs

Explore the tools built by this company.

BIMind

BIMind turns a complex IFC file into something anyone can interrogate, on any device, in plain English in seconds. Backed by 100+ specialized AI agents. Core Capability : 3D Visualization - Browser-based IFC viewer - Orbit, zoom, pan - Exploded view by floor - Clipping planes on any axis AI Conversation - Natural language queries - Cost & quantity estimates - Create/modify IFC models - Thread continuity (memory) - GPT-4o, Claude, Gemini Model Analysis - Point-to-point measurement - Annotation pins (JSON export) - Model comparison & diff - Element properties inspector Compliance Checking - Fire code validation - Accessibility standards

Case studies

View featured case studies from IntentoLabs.

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