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This AI startup says it can generate permit-ready blueprints in minutes

Blueprints AI, a bootstrapped startup based in Santa Monica, developed software that produces code-compliant construction blueprints from a photo, PDF, or sketch.

Al Drams, an architect, had a vision for technology that could generate architectural blueprints, but it took nearly two decades to become reality. The idea came to him following OpenAI's release of ChatGPT in 2022. Within six months, he launched Blueprints AI, a startup that uses AI to produce permit-ready architectural construction blueprints.

Founded in 2025 with co-founder Coco Cao in Santa Monica, the startup was selected for the 2026 Startup Battlefield 200 cohort. Drams studied architecture at the University of Tehran and later completed his Ph.D. on digital design in Switzerland. He moved to the US and opened an architecture firm in 2018, later adding a construction business.

Blueprints AI's software will unveil a more capable second-generation version at Disrupt, which will take over the repetitive drafting work that consumes most of an architect's time. Drams says architects spend 80% of their time on drafting and only 20% on design, a problem Blueprints AI aims to solve. The startup's first-generation software costs $3,200 to $8,500 a month, while custom pricing for enterprises is also available.

The second-generation software will allow users to design every aspect of a building at once, including architecture, structural, mechanical, electrical, plumbing, and interior design. One design change will automatically update the entire project and be checked against local building codes. The technology doesn't replace licensed architects, who will still review the documents before submitting them for permits.

Blueprints AI targets professional architecture, engineering, and design firms, as well as developers and real estate owners. The startup offers its software as a subscription, with a potential one-time flat-fee option for single-project use.

Written by urgent.news from TechCrunch's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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