Swiftbuild provides an AI‑native platform that automates code‑compliance analysis of CAD/BIM submissions and streamlines plan‑review workflows for municipal planning and permitting agencies. By configuring the system to local building, zoning and environmental codes and integrating with existing GIS and permitting tools, it surfaces potential violations in real time, reducing review cycles from weeks to minutes and cutting rework and cost overruns.
Funding
Funding not disclosed
Founders
Product
Problem
Local government planning and permitting processes are hampered by manual compliance checks, fragmented workflows, and outdated software, leading to long review cycles, rework, and cost overruns for both agencies and developers.
Solution
Swiftbuild delivers an AI‑native platform that automates code‑compliance analysis and streamlines plan‑review workflows for public‑sector agencies. The system ingests CAD/BIM files, applies jurisdiction‑specific building codes, and surfaces potential violations in real time, allowing staff to address issues early. By configuring the AI to each locality’s rules and integrating with existing GIS and permitting systems, the platform reduces review times from weeks to minutes while preserving human judgment through an “AI‑in‑the‑loop” interface. The resulting faster approvals lower construction financing costs, cut rework, and generate measurable annual savings for municipalities.
Target Audience
Primary customers are municipal planning and building departments, county permitting offices, and related public‑sector agencies that manage land‑development and construction approvals.
Features
- Automated code‑compliance checks on CAD/BIM submissions using trained AI models
- Jurisdiction‑specific configuration that encodes local building, zoning, and environmental codes
- Real‑time issue flagging with visual annotations and suggested remediation steps
- Integration hooks for GIS, permitting, and document‑management systems via APIs
- Agentic AI assistant that surfaces relevant guidance to reviewers while preserving final decision authority
- Scalable cloud architecture that learns from each review to improve accuracy over time