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.
A newly formed technology company announced the launch of an AI-driven platform aimed at automating the process of creating construction takeoffs from PDF plans. The product initially targets electrical takeoffs and is built with computer vision and generative AI components to interpret plan legends and the symbols used on architectural drawings.
The platform reads PDF construction plans, identifies industry symbols and legend items, and produces lists of required materials and labor cost estimates for electrical work. The company reports that the tool can replace many hours of manual counting and interpretation and can help reduce errors common in traditional takeoff workflows.
Developers and estimators frequently spend large blocks of time manually marking plans and compiling counts. The startup says its product automates that labor, allowing estimating teams to shift toward higher-value tasks such as validation, pricing strategy, and subcontractor coordination.
The company was founded by a contractor and entrepreneur who runs a design-build firm that focuses on housing and renovations. The founding team also includes an AI and machine learning engineer with experience in government and defense projects, and a technologist focused on business automation tools. The company has an early strategic partnership with a business accelerator that will provide help with business development, sales, marketing and executive coaching. An executive from that accelerator will serve as a strategic advisor.
The platform is currently in early pilot use with selected contractors. Those pilot customers are testing the system to see how it fits into preconstruction workflows and whether it reduces takeoff errors and turnaround time. The company describes the product as showing promise but still in early stages of deployment and refinement.
In the coming year, the team plans to extend the platform beyond electrical work to include plumbing, framing and HVAC trades. The company also plans to continue refining its models to improve adaptability across different plan formats and project types, with a long-term aim to expand AI-support for broader preconstruction and project-management tasks like cost estimation and resource allocation.
The company highlighted a broader industry challenge as part of its launch materials: an estimated large portion of the current construction workforce is expected to retire within the next few years. The firm framed automation as one way to address labor shortages by freeing experienced staff from repetitive tasks and allowing less-experienced staff to handle higher-level responsibilities sooner.
According to the company, the electrical takeoff module can automatically produce a comprehensive list of materials and a labor cost breakdown, which should speed preconstruction work, help produce faster project timelines, and support more accurate cost projections. The company also said it is actively seeking additional contractors to join pilots and partnerships to broaden industry reach and improve the product.
The tool combines image analysis to read and interpret plan drawings with generative models that translate symbol detections and layout information into structured takeoff outputs. The approach is intended to handle the two main tasks in digital takeoffs: recognizing items on a page and converting those recognitions into bill-of-materials and labor estimates.
The company is soliciting beta testers and partners while it continues to refine model performance and usability. It described the current platform as being in initial commercial stages and set to expand trade coverage during the next 12 months.
The platform automates the extraction of item counts, material lists and labor cost estimates from electrical plan PDFs.
Electrical takeoffs are supported now. Plumbing, framing and HVAC are planned for rollout within the coming year.
Selected contractors are piloting the system to evaluate workflow fit, accuracy and the potential to reduce manual errors.
The product uses computer vision for plan interpretation and generative AI to turn detections into structured takeoff outputs.
The company positions the tool as an automation aid to speed up repetitive tasks, allowing estimators to focus on validation, pricing and project planning rather than replacing them.
The company is seeking partners and beta testers; interested firms are invited to reach out through the channels listed in the company’s launch materials.
| Feature | What it does |
|---|---|
| Core technologies | Computer vision and generative AI to read plans and produce structured outputs |
| Initial focus | Automating electrical takeoffs from PDF plans |
| Outputs | Material lists and labor cost estimates |
| Expansion plans | Plumbing, framing and HVAC in the next 12 months |
| Pilot status | Active pilots with select contractors testing accuracy and workflow fit |
| Expected benefits | Faster preconstruction, fewer manual errors, improved cost projections |
| Industry context | Designed to help address labor shortages as experienced staff retire |
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