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AutoSitu

AI-native workspace for municipal development reviews

AI agents platform that automates site plan review, zoning compliance, building code checks, and permit approvals for municipalities and developers. Reduces review cycles by up to 90% through parallel analysis of plans against local regulations.

Y Combinator W26 (funding amount not publicly disclosed) raisedEarly Stage
Founded 2025 · 11 municipalities including San José, Seattle, Long Beach, Boston, Coral Gables
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WHY IT EXISTS

Why This Tool Exists

The Problem

Municipal development review processes are slow and labor-intensive, with planning departments manually analyzing site plans, checking zoning compliance, and verifying building codes across multiple departments, taking weeks to complete reviews. Cities struggle with inconsistent review standards and developers face unpredictable approval timelines.

The Solution

AI agents analyze site plans against local zoning codes and building ordinances in parallel, identifying compliance issues in minutes rather than weeks. The platform converts AEC drawings into structured data, applies local codes automatically, and escalates judgment calls to human planners while handling objective compliance checks.

USAGE

How You Use It

Delivery Method
SaaS
Integrations
Not publicly specified
Disciplines
Architecture, Civil Engineering
Workflows
Data & Automation, Planning & Feasibility, Code & Compliance
Project Phases
Construction Documentation, Bidding/Procurement
Project Types
Commercial, Residential, Healthcare, Education, Infrastructure, Mixed-Use, Industrial, Hospitality, Institutional
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Site plans, Building drawings, Local zoning codes
Optional:Development applications, Supporting documentation
Formats:PDF, DWG (rolling out), DXF (rolling out), BIM models (rolling out)
Output
What you get
Format:Compliance reports with identified issues and recommendations
Fields:Zoning compliance status, Building code violations, Issue locations, Recommended corrections, Review timeline
Algorithm
How it works
Model:Proprietary AI agents (multi-agent system architecture)
Accuracy:Claims to identify compliance issues with human-level reasoning (methodology not published)
Privacy
How your data is protected
Retention:Not publicly specified
Training:Does not train AI models on proprietary data without explicit permission
Compliance:Enterprise-grade encryption for data in transit and at rest
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Municipal site plan review automation
  • ·Zoning compliance verification for developers
  • ·Building permit application processing
  • ·Multi-departmental development review coordination
  • ·Regulatory compliance checking for planning departments
PRICING

Pricing

Free
Not available
Pro
Contact for pricing
Enterprise
Contact for pricing
Sources & Research NotesResearch date: 2026-02-01
Data Sources (4)
Fields Checked (9)
problem, solution, deliveryMethod, maturityStage, yearFounded, customerBase, team-background, core-features, supported-formats
Not Found (7)
pricing, api-documentation, privacy-policy, detailed-funding, compliance-certifications, algorithm-specifications, integrations
About this research: This record summarizes the cited sources and fields checked. A research date does not establish hands-on testing. Consult the original sources for current details and limitations.
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