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TestFit

AI-powered real estate feasibility platform for site planning

Generative design platform that automates site planning and feasibility studies for real estate development. Instantly generates thousands of optimized building layouts based on zoning, parking, unit mix, and financial constraints, allowing teams to evaluate design options in seconds.

$22M raised 📈 Growth Stage

Founded 2016 • 6,600+ users evaluating 1,500+ deals per week

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Why This Tool Exists

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The Problem

Real estate development teams spend weeks manually creating and comparing site plans, tediously calculating parking ratios, unit mixes, and yield metrics. Traditional feasibility analysis delays crucial go/no-go decisions and wastes resources on designs that may not maximize land value.

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The Solution

Automates site planning using generative design to create thousands of layout options in seconds. Optimizes for zoning compliance, parking efficiency, and financial metrics (yield on cost, cut/fill volumes). Enables teams to test design variations and make rapid feasibility decisions. Integrates directly with Revit to streamline transition from feasibility to design documentation.

How You Use It

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Delivery Method

SaaS Plugin

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Integrations

Revit AutoCAD SketchUp Zoneomics ESRI Thornton Tomasetti TT Core Studio

Disciplines

Architecture, Owner/Developer, Civil Engineering

Project Phases

Pre-Design, Schematic Design, Design Development

Project Types

Commercial, Residential, Mixed-Use, Industrial

Data Transparency

Exactly what this tool uses and how

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Input

What it needs

Required: Property parcel or site boundary, Zoning parameters, Unit mix or building type requirements

Optional: 3D terrain/topography data, Parking requirements, Cost assumptions, Schedule integration

Formats: CSV, Drawing files, Map data (GeoJSON), Parcel shapefiles

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Output

What you get

Format: Interactive design scheme comparisons with cost and efficiency metrics

Fields: Building layouts and floor plans, Parking configuration with stall counts, Net rentable square feet (NRSF) and efficiency ratios, Yield on cost and financial metrics, Cut and fill volumes for earthwork cost estimation, Unit mix and apartment count variations

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Algorithm

How it works

Model: Proprietary generative design engine (not machine learning-based)

Accuracy: Not publicly specified (claims algorithm designs building diagrams in milliseconds)

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Privacy

How your data is protected

Retention: Project-based retention duration (specific period not publicly specified)

Training: Not publicly specified

Compliance: Standard Contractual Clauses for international data transfers, GDPR and CCPA compliance stated

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API

Integration

Endpoint: Contact vendor for API access

Method: Not publicly documented

Use Cases

• Rapid site feasibility and go/no-go decision making before land optioning
• Zoning compliance testing and highest-and-best-use optimization
• Multi-family residential development with unit mix variations
• Mixed-use and commercial project feasibility analysis
• Parking efficiency optimization and cost estimation
• Earthwork cost estimation through cut/fill volume analysis
• Architect generation of multiple code-compliant design schemes for client presentation

Pricing

Free

Free trial available (no credit card required)

Pro

Urban Planner: $100/month, Data Maps: $400/month, Site Solver: $10,000/year (all billed annually)

Enterprise

Enterprise: Custom pricing with volume discounts, SSO, and quarterly business reviews

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📚 Research Sources & Data Quality Last verified: 2026-02-01

Data Sources (9)

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Verified Data (19)

problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, customerBase, fundingTotal, input-required, input-optional, output-fields, output-structure, algorithm-approach, control-features, pricing-all-tiers, useCases

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Not Found (6)

algorithm-model-specific, algorithm-accuracy-metrics, privacy-data-retention-days, api-documentation, soc2-certification, iso27001-certification

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.