Structured AI📐: Agentic workforce for construction design engineering
Our AI workforce generates design documents and checks them for errors, right inside your existing software.
TL;DR
Structured AI is building the AI workforce for construction design engineering, starting with AI agents that perform quality control on technical documents and drawings. Our agents learn your standards, apply the right building codes, and automatically review your drawings, so you see fewer clashes, fewer inconsistencies, and fewer costly RFIs and change orders.
- ⚙️ Automates QA/QC across mechanical, electrical, structural and more
- 🧩 Used by multi-disciplinary design firms to deliver projects faster with less risk
- 🚀 Mission: Free engineers to focus on creative design, not repetitive admin
Launch Video: https://youtu.be/CRFsqOTynng
❌ The Problem
The construction industry's reliance on manual "spot-checking" for design errors costs $177 billion annually to fix mistakes that are discovered too late.
Senior Engineers spend up to 50% of their time cross-referencing 100-page drawing sets against 2,000-page building regulations by hand. This process is slow, tedious, and unreliable.
Errors that are missed become exponentially more expensive to correct once construction is underway, causing massive project delays and budget overruns.
⚙️ The Solution
Structured AI is the AI Quality Assurance platform.
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Proprietary Vision & Agents: We trained a foundational vision model on thousands of engineering symbols to read plans like an expert.
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100x Faster, 150% More Errors: Our AI checks 100-page blueprints against 2,000 pages of building codes in minutes.
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Cross-trade Checks: Learns firm standards to detect inconsistencies across documents, drawings and Revit models, reducing cross-trade clashes before they occur.
👷♀️ The Team
The team is made up of Oxford University–trained AI researchers with deep experience building software tools for AEC and enterprise automation, having developed and scaled in-house AI tools at Syska Hennessy Group, a top US MEP (mechanical, electrical, plumbing) engineering firm.
- Brandon (CTO): Authored papers for NeurIPS and ChromaDB (reviewed by Stanford's AI Lab) and created the first open-source RAG chunking evaluation framework.
- Raymond (CEO): Built automation at Goldman Sachs and the London Stock Exchange; implemented an AI system at a £1B VC that increased deal flow 20×.
- Issy (COO): First undergrad Director at Oxford's VC Fund, led investments later backed by a16z and Tim Draper; previously investment banking at Greenhill.
🏗️ Why Construction Engineering?
Brandon started coding and making games when he was 12. At 17, a YouTube video he made demonstrating a fighter jet trained with deep reinforcement learning to dodge missiles went viral. This led to him being scouted by a US construction contractor to apply that same algorithm to MEP pipe routing optimization. He then spent the next six years, throughout high school and university, contracting and building AI tools for the construction and engineering industry. He later led innovation and scaled AI tools in-house at a top US engineering firm, ultimately spinning out with his team to form Structured AI.
Raymond initially pursued architecture and engineering, but was talked out of the profession during an internship. Junior architects warned him about the extensive manual "grunt work" that defined their roles, a prospect that deterred him so much he switched his studies to Maths & Stats at Oxford. He now views his work freeing engineers from these very tasks as a full-circle moment, allowing them to focus on their passions.
🙏 Our Ask
If you lead mechanical, electrical, civil, or structural design teams and want to automate documentation or QA workflows, we’d love to show you Structured AI.
👉 Book a call: https://www.getstructured.ai/
📩 Contact: info@getstructured.ai