AI-powered software analyzes PDF electrical plans and generates material and labor lists for estimating teams.
United States, August 18, 2025
A new construction tech startup unveiled an AI-powered platform that automates electrical takeoffs from PDF construction plans. The system combines computer vision to read drawings and industry symbols with generative AI to assemble comprehensive bills of materials and labor cost estimates. Pilots with select contractors are underway to validate workflow improvements and accuracy gains. The tool aims to cut manual estimating hours, help mitigate workforce shortfalls caused by retirements, and speed preconstruction timelines. The company plans to expand support to plumbing, framing and HVAC and is seeking beta partners to refine models and trade-specific features.
What happened: A newly formed construction tech firm announced the launch of an AI-powered platform designed to automate electrical takeoffs from PDF construction plans. The company said the tool can read plan legends and industry symbols, then produce a detailed list of required materials and labor costs, aiming to cut the time and effort estimators now spend on manual work. The announcement was made in the United States on August 17, 2025.
The construction industry faces growing pressure to speed up preconstruction work and improve cost accuracy as many experienced workers approach retirement. The release cited an industry estimate that roughly 40% of the current construction workforce could retire in the next few years. Builders and estimating teams stand to gain immediate time savings if repetitive takeoff tasks are automated, which could help offset workforce shortages and keep projects on schedule.
The platform combines computer vision to read and interpret drawings with generative AI to assemble lists and cost items. It is built to identify common architectural plan legends and industry-standard symbols so that it can reliably extract counts and specifications from PDF sheets. The company reports the electrical-focused tool already generates complete bills of materials and corresponding labor cost estimates from those plans.
The company says its flagship electrical-takeoff tool lowers the hours needed for manual takeoffs and improves the accuracy of resulting estimates. The platform is currently in early stages but is being piloted by a selection of contractors who are testing whether the system improves workflow and reduces errors during the estimating phase of projects.
The startup was founded by a contractor and entrepreneur who leads a design-build firm that focuses on affordable housing and renovations. The founding team includes a seasoned AI and machine learning engineer with experience in defense and government work and a creative technologist who has built business automation tools for other firms. The team says those skills were key in creating the platform’s core AI capabilities and bridging the technology to real business needs.
The company has a strategic relationship with a business accelerator that will provide guidance in business development, sales and marketing, and executive coaching. An executive from the accelerator will serve as a strategic advisor to the startup to help scale operations and broaden market reach.
Over the coming year, the firm plans to expand the platform beyond electrical work to add plumbing, framing and HVAC trades. The company is also exploring ways to make its AI models more adaptable to different project types and drawing styles. In the longer term, the startup aims to broaden its AI toolset to support project management, cost estimation and resource allocation tasks.
While still in pilot mode, the company is seeking partnerships and beta testers to refine the system and extend its reach across the construction sector. Early users are expected to help fine-tune model accuracy, validate real-world workflows and identify trade-specific features needed for broader adoption.
The announcement did not include public pricing, detailed accuracy metrics, or a full rollout schedule. It also did not list specific contractor names participating in pilots or disclose exact customer outcomes beyond general claims of time savings and improved accuracy.
The platform aims to reduce routine estimating work by using computer vision and generative AI to translate PDF plans into actionable material and labor lists. If the pilot results scale, the tool could relieve some pressure on estimating teams and help firms respond to workforce shifts while shortening preconstruction timelines and tightening cost projections.
It reads PDF construction plans, recognizes electrical symbols and legends, and automatically produces lists of required materials and labor cost estimates for electrical work.
The platform currently focuses on electrical takeoffs. The company plans to expand support to plumbing, framing and HVAC within the next year.
The firm reports improved accuracy compared with manual takeoffs, but full accuracy metrics were not published. Pilot users are helping to validate and refine model performance.
Select contractors are running pilot programs that evaluate workflow improvements and error reduction during the estimating process.
At the time of the announcement the product is in early stages and actively seeking partners and beta testers. Public availability and pricing were not announced.
The system uses computer vision to interpret drawings and generative AI to assemble parts lists and cost items.
With many skilled workers nearing retirement and estimating remaining time-consuming, automation can help firms save time, reduce errors and maintain project schedules as labor availability changes.
| Feature | Description |
|---|---|
| Primary function | Automated electrical takeoffs from PDF plans |
| Core technology | Computer vision combined with generative AI |
| Outputs | Comprehensive materials lists and labor cost estimates |
| Pilot status | Being tested with select contractors |
| Near-term expansion | Plumbing, framing and HVAC trades planned within one year |
| Team strengths | Construction expertise plus AI/ML and automation engineering |
| Strategic support | Business accelerator partnership for go-to-market support |
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