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AI-Powered Preconstruction Platform Wyre Raises $5M to Analyse Construction Documents

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By PropTechBuzz
9/11/2026

Construction technology startup Wyre has raised $5 million in pre-seed and seed funding to transform how contractors analyse construction drawings, specifications, and shop drawings during the preconstruction process.

The company was founded by Sunil Dorairajan, who previously founded Pype, a construction technology company acquired by Autodesk in 2020. After spending years working in preconstruction and construction operations, Dorairajan returned to the sector with Wyre, aiming to address one of the industry's most time-consuming challenges: extracting critical project information from thousands of pages of documents under tight deadlines.

Turning construction documents into actionable scopes

Wyre describes itself as an AI-powered document intelligence platform designed to scan drawings and specifications and convert them into structured scopes, risk insights, and traceable references.

Its flagship Wyre Scopes platform uses machine learning to analyse complete document sets, identify scopes of work, and produce traceable scope packages that preconstruction teams can review and refine.

The goal is to reduce the manual effort involved in reviewing construction documents while helping contractors identify scope gaps and potential risks before they become costly problems during construction.

Wyre also offers Wyre Check, an AI-powered service designed to analyse construction documents and shop drawings for potential clashes.

The company says its models have been trained using proprietary datasets and information tagged and validated by construction subject-matter experts. This expert-validated data forms an important part of Wyre's intellectual property and is intended to differentiate its platform from general-purpose document analysis tools.

Built around real construction workflows

Wyre is targeting contractors and preconstruction teams, but the platform can also be used during project operations.

According to the company, its technology can support activities including scope writing, bidding, buyout, document review, and identifying conflicts before they affect projects.

The startup is already being tested by approximately a dozen contractor customers at different stages of deployment.

Rycon Construction project manager Dylan John said the platform has been used by its operations team for scope writing and buyout, helping surface scope gaps and conflicts earlier in the project lifecycle.

Backed by construction technology investors

The $5 million funding round was led by Ironspring Ventures, with participation from WND Ventures, the corporate venture arm of DPR Construction, and the Virginia Innovation Partnership Corporation (VIPC).

The round also attracted angel investment from construction technology executives including Amar Hanspal, CEO of Motif and former Autodesk co-CEO, Rajesh Ram, co-founder and chief growth officer of Egnyte, and Joseph Khoury, vice president of Preconstruction and co-founder of MCN Build.

Ironspring Ventures co-founder and general partner Ty Findley said preconstruction is where high-stakes decisions are made and project margins are established, highlighting the scale of the problem Wyre is targeting.

A competitive AI construction market

Wyre is entering a rapidly developing construction AI market, competing with solutions such as Procore's DataGrid, Trunk Tools, and Autodesk's Pype.

The company's advantage will depend on whether its construction-specific models and expert-validated data can consistently deliver more useful results than broader document intelligence platforms.

Wyre has also strengthened its technical leadership with Varada Pyda as chief technology officer. Pyda previously led engineering at Pype and later headed AI solutions at Autodesk Construction Solutions before joining Dorairajan at Wyre.

With the new funding, Wyre aims to continue developing its AI platform and expand its adoption among contractors looking to make preconstruction faster, more accurate, and less dependent on manual document review.

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