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Autodesk Insight

AI-powered building performance analysis and carbon impact simulation

Cloud-based energy analysis and carbon modeling tool integrated with Revit. Analyzes embodied and operational carbon, energy consumption, and daylighting to enable architects and engineers to make data-driven design decisions. Built on DOE-2.2 and EnergyPlus simulation engines with real-time performance feedback.

Part of Autodesk ($18B+ valuation) raised Established
Founded 2015 · 100,000+ Revit users with access; active adoption by top AEC firms (specific count not disclosed)

Why This Tool Exists

The Problem

Architects and engineers lack real-time visibility into energy and carbon impacts of design decisions until late in the design process. Manual energy analysis workflows are time-consuming and delayed feedback prevents exploration of design alternatives. This results in buildings that miss sustainability targets and exceed operational costs.

The Solution

Provides instant energy simulation and carbon analysis directly in Revit, analyzing embodied and operational carbon impacts from early design stages. Uses DOE-2.2 and EnergyPlus simulation engines to run hundreds of design iterations in seconds, enabling architects to visualize performance trade-offs across HVAC systems, envelope design, materials, orientation, and renewable offsets.

How You Use It

Delivery Method
SaaSRevit PluginWeb Dashboard
Integrations
RevitFormIt Pro
Disciplines
Architecture, Engineering, Sustainability
Project Phases
Schematic Design, Design Development
Project Types
Commercial, Residential, Mixed-Use, Healthcare, Education, Institutional

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required: Revit BIM model, Building envelope definition
Optional: HVAC system details, Lighting specifications, Material library, Location/climate data, Renewable energy systems
Formats: Revit (.rvt), Energy Analytical Model
Output
What you get
Format: Interactive carbon analysis dashboard and energy reports
Fields: Total carbon emissions (embodied + operational), Energy consumption by end use (HVAC, lighting, plug loads), Daylighting analysis (daylight autonomy, annual sunlight exposure), Heating and cooling loads by zone, Energy costs and benchmarking vs ASHRAE 90.1, Carbon reduction scenarios and sensitivity analysis, Solar insolation visualization on building surfaces
Algorithm
How it works
Model: DOE-2.2 and EnergyPlus simulation engines; machine learning regression analysis for parametric scenario generation
Accuracy: Industry-standard simulation engines; accuracy dependent on input model detail and weather data quality
Privacy
How your data is protected
Retention: Project data stored in user account; user can delete projects at any time
Training: Not publicly specified
Compliance: SOC 2 (Autodesk maintains SOC 2 certification), GDPR compliant, ISO 27001 (Autodesk certified)
API
Integration
Endpoint: Contact vendor for API access
Method: Not publicly documented

Use Cases

  • · Early-stage design exploration comparing envelope, HVAC, and renewable energy scenarios
  • · Embodied carbon tracking and optimization during design development
  • · Daylighting analysis to meet LEED and WELL certification requirements
  • · ASHRAE 90.1 compliance verification and energy cost benchmarking
  • · Multi-option design comparison for sustainability-driven decision-making
  • · Portfolio-level carbon goal tracking across multiple projects

Pricing

Free
30+ day free trial included with Revit subscription
Pro
$335/month or $2,675/year (included with Revit subscriptions)
Enterprise
Custom pricing for multi-user teams and advanced features
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Research Sources & Data Quality Last verified: 2026-04-04
Verified Data (14)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, pricing, algorithm-engines, output-fields, useCases, compliance-certifications
Not Found (5)
exact-customerBase-count, api-documentation, webhook-support, data-training-policy, data-retention-days
Our Commitment: We only include verified data from official sources. If information isn't publicly available, we mark it as "Not publicly specified" rather than guessing.