UrbanAgentOpen Platform
Investor and customer validation edition

From Parcel to Investment Decision in Minutes

UrbanAgent converts parcels, regulations, economics and risk signals into explainable development scenarios and investment-grade feasibility outputs.

Built for developers, architects and municipalities
Explainable scenarios, not black-box output
Netherlands-first compliance and site logic

Product workflow

AI Feasibility Report

Netherlands first
01
Stage 1
Parcel
02
Stage 2
AI Agents
03
Stage 3
Knowledge Graph
04
Stage 4
Optimization Engine
05
Stage 5
Investment-grade Feasibility Report
Lead time
Minutes
Output
Scenario set
Mode
Human review

Product Experience

A feasibility dashboard built for real development decisions.

UrbanAgent turns a parcel into scenarios, financial metrics, compliance signals and an explainable recommendation.

Parcel Analysis

Deventer infill site

Live preview

Recommended scenario

Balanced

Estimated ROI

18%

Compliance

91%

Confidence

84%

Scenario B recommended

Highest risk-adjusted ROI with acceptable parking strategy and conditional compliance pass.

8,200 m2
EUR11M profit
Review ready
Agent execution timeline
MarketAgent completed
ParkingAgent detected deficit
ComplianceAgent issued conditional pass
FinancialAgent calculated ROI
OptimizationAgent selected Scenario B

Topology-first product flow

Validate the parcel before floor planning.

UrbanAgent now treats the cadastral boundary, buildable envelope and hard constraints as the first-class workflow. A centered floorplate is rejected before it can be called viable.

Primary workflowParcel → envelope → topology
Hard constraint behaviorBlock / reject
Floor planning gateValid topology only
Active layers
Cadastral parcelHard
Buildable envelopeActive
Topology scenariosRanked
Rejected candidatesVisible
Solver gates
1. Validate parcel boundary
2. Generate buildable envelope
3. Rank topology scenarios
Loading topology feasibility...
Topology canvasHard constraints visible
No topology scenario is ready for floor planning. Review parcel boundary and envelope first.
Inspector
Workflow stage
loading
Recommended topology
Envelope first
Buildable envelope
calculating
Floor planning gate
blocked
Topology-first rule
A typical floor can only be generated after parcel and buildable-envelope validation.
Scenario decision

Generate Chord Bar, L-Courtyard and Compact Point Block before floor planning.

Next: parking / bike / green / fire access

Sample Output

Make the output feel review-ready for a real project team.

The landing page should preview the first commercial deliverable: an AI Feasibility Report that a planner, architect, developer or municipality can scan immediately.

UrbanAgent AI Feasibility Report

Deventer Residential Infill Site

Market potential

Strong

Compliance risk

1 review item

Recommendation

Scenario B

Scenario comparisonConfidence 84%
ScenarioUnitsParkingFARHeightSolarViolations
A1121432.724 m82%2
B961182.321 m89%0
C841062.018 m92%0
BVO
13,420 m2
Walkability
8.4 / 10
Review item
Access turning radius at south entry

Review contents

Parcel and cadastral context
Road hierarchy and access logic
Parking requirement and deficit analysis
Height, setback and daylight constraints
Financial feasibility and cost envelope
Risk-adjusted recommendation
Decision summary
Scenario B is selected because it preserves compliance, improves solar performance, and reduces parking pressure with acceptable density.

Meet the First Product

AI Feasibility Report

Transform any parcel into an investment-grade development report.

Preview

Investment-grade report preview

Market Potential
Compliance
Parking Analysis
Risks
Financial Metrics
Recommended Scenario
Recommended scenario: Balanced density, 18% ROI, confidence 84%.

Traditional feasibility studies are fragmented and slow.

Fragmented workflows

Excel, GIS, PDFs and external consultants create friction across every feasibility cycle.

Weeks of analysis

Site feasibility reviews often take 2-6 weeks before a confident decision is possible.

High uncertainty

Critical development decisions are made with incomplete context and limited scenario testing.

From Data to Decisions

A product output designed to be useful on day one.

Site Screening

Instant parcel analysis.

Development Scenarios

Multiple alternatives.

Compliance Review

Bbl, Omgevingswet and NEN.

Financial Feasibility

ROI and IRR.

Risk Assessment

Market and environmental risks.

Explainable Decisions

Human-in-the-loop.

Example Development Scenarios

Compare development outcomes before committing to a path.

Scenario
Units
ROI
Risk
Conservative
72
14%
Low
Balanced
96
18%
Medium
Aggressive
124
23%
High

Recommended

Balanced Scenario

Confidence 84%

96 units
18% ROI
Medium risk profile

Human-in-the-loop

AI Assists. Humans Decide.

UrbanAgent augments professionals. Architects, developers and municipalities remain in control of final decisions.

AI
Knowledge Graph
Optimization
Human Review
Decision

Pilot Program

Looking for Design Partners

UrbanAgent is currently onboarding selected developers, architects and municipalities for pilot projects.

Early access
Direct feedback loop
Custom workflows
Priority support

Credibility

Built for Real-World Development

Open Geospatial Data

PDOK, BAG, BGT, AHN and OSM integrated into one development context.

Explainable AI

Confidence scores and human review keep recommendations interpretable.

Dutch Compliance Layer

Purpose-built around Bbl and the Omgevingswet.

Multi-Agent Architecture

Specialized AI agents collaborate across planning, market, risk and finance.

Optimization Engine

Scenario evaluation built for tradeoff analysis, not static reporting.

Open Architecture

API-first platform designed to plug into professional workflows.

Spatial Intelligence Stack

Research Foundation

UrbanAgent orchestrates open weights and spatial embeddings developed by leading global AI labs.

Research ecosystem informing the UrbanAgent spatial intelligence stack

How It Works

Show inputs, constraints, processing logic and outputs in one operational flow.

Step
Inputs
Processing
Outputs
01
Parcel geometry, zoning, typology target
Ingest site, cadastral and planning context
Base site model
02
Mobility, parking, solar, access, green targets
Run constraint analysis and violation detection
Constraint register
03
Scenario parameters and density assumptions
Compare alternatives across FAR, units, cost and risk
Scenario matrix
04
Preferred alternative
Produce review-ready recommendation and report
Decision package
Geospatial Foundation Models
Multi-Agent AI
Knowledge Graph
Optimization Engine
Explainable AI

Technology

Enough technical depth to signal substance, without hiding the product.

UrbanAgent combines geospatial models, multi-agent reasoning, a knowledge graph and optimization into one explainable decision layer for real estate development.

Social Proof Placeholder

Designed for

Developers
Architects
Municipalities
Investors
Consultants

Future Vision

Toward an Urban Development Operating System

UrbanAgent is designed to evolve from AI feasibility reports into a full decision intelligence platform for real estate development.

FAQ

Questions from early design, investment and public-sector conversations.

Waitlist

Join the validation pipeline

Tell us what kind of development decisions you want UrbanAgent to support, and we will follow up with the right next step.

Selected pilot access for developers, architects and municipalities.
Priority goes to teams with active Dutch development workflows.
We respond with the most relevant next step: pilot, demo or sample report.