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SWAPP AI

AI-powered architectural documentation automation

AI co-pilot platform that learns architectural firms' standards and automates creation of construction documents, including floor plans, elevations, and MEP layouts from schematic designs through construction documentation.

$11.5M raisedGrowth Stage
Founded 2017 · 15+ architecture firms including MYS Architects (Israel's largest), MOREgroup, SNHA, VLK Architects
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WHY IT EXISTS

Why This Tool Exists

The Problem

Architectural firms spend weeks manually creating detailed construction documents from schematic designs, requiring consistent application of firm-specific standards, annotation practices, and BIM conventions. This repetitive work delays project schedules and prevents architects from focusing on creative design work.

The Solution

SWAPP learns from a firm's historical projects to extract design patterns and standards, then automatically generates detailed Revit deliverables (floor plans, elevations, annotations, schedules) that comply with firm-specific conventions. The platform transforms schematic designs into construction documentation sets in days rather than weeks.

USAGE

How You Use It

Delivery Method
SaaSAPIPlugin
Integrations
RevitAutoCADAutodesk BIM 360Autodesk Construction Cloud (ACC)
Disciplines
Architecture, Construction
Workflows
Data & Automation
Project Phases
Schematic Design, Design Development, Construction Documentation
Project Types
Commercial, Residential, Mixed-Use, Institutional, Industrial
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Schematic design (Revit model), Historical project examples (for AI training)
Optional:Project schedule, Design guidelines, BIM standards documentation
Formats:RVT (Revit), DWG, IFC
Output
What you get
Format:Revit construction documents with AI-generated annotations and layouts
Fields:Floor plans with annotations, Elevations and sections, Door and window schedules, Finish schedules, MEP coordination documentation, Custom callouts and dimensions
Algorithm
How it works
Model:Proprietary Design Decision Language (DDL) + machine learning on firm-specific standards
Accuracy:Automates up to 80% of documentation tasks; claims 50% reduction in documentation time (methodology not published)
Privacy
How your data is protected
Retention:Project-based retention; data retained as long as necessary to fulfill service purposes and comply with legal obligations
Training:Not publicly specified whether client data is used to train general models; firm data used only for client-specific model training
Compliance:ISO 27001 certified, GDPR compliant with standard contractual clauses for EU data transfers
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Automate creation of construction document sets from schematic designs
  • ·Maintain consistency across multiple projects using firm standards
  • ·Reduce manual annotation and schedule creation time
  • ·Accelerate design development to construction documentation workflow
  • ·Generate MEP coordination documentation
  • ·Enable architects to focus on design instead of documentation
PRICING

Pricing

Free
No free tier
Pro
Custom pricing based on square footage and vertical (industry type)
Enterprise
Enterprise pricing available with dedicated consulting
Sources & Research NotesResearch date: 2026-01-31
Data Sources (10)
Fields Checked (16)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, fundingTotal, customerBase, input-formats, output-fields, useCases, pricing-model, compliance-iso27001
Not Found (7)
api-documentation, algorithm-accuracy-methodology, data-training-policy, data-retention-period, soc2-certification, exact-customer-count, rate-limit-specifications
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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