What is Drawer AI?
Manual electrical takeoff and estimating are time-consuming and prone to errors, directly impacting project bids and profitability. Electrical estimators need tools that deliver speed and precision without compromising detail. Drawer AI is an AI-powered software specifically designed to streamline and accelerate the electrical estimating process for electrical subcontractors and contractors. It transforms how you handle drawing analysis, device quantification, and branch routing, giving you back valuable time.
Key Features
Drawer AI equips you with powerful AI-driven features designed to tackle the most challenging parts of electrical estimating:
⚡ Generative Takeoff & Accurate Quantification: Instantly analyze PDF drawings to automatically detect and quantify lighting fixtures and power devices. Leveraging in-house developed AI technology, Drawer AI performs tedious counting and classifying for you in minutes, providing accurate device counts and automated tag linking for features, panels, and circuits. You retain control with built-in QA tools for quick review.
🗺️ Automated Branch Routing & Wire Sizing: Eliminate hours of manual routing. Drawer AI's AI engine tests thousands of potential routes to identify efficient pathways. It automatically performs wire sizing, including voltage drop calculations, delivering highly detailed branch routing layouts in minutes, not hours.
🧩 Automated Stitching: Seamlessly combine multiple plan sheets from your PDFs into a single, unified floor layout. This ensures accuracy and consistency when working with split drawings, preparing your project for accurate routing with just a few clicks.
How Drawer AI Solves Your Problems
Drawer AI directly addresses the inefficiencies and pressures of traditional electrical estimating:
Rapid, Reliable Takeoffs: Instead of manually counting thousands of devices across numerous drawings, upload your PDFs and let Drawer AI provide accurate quantifications in minutes. This drastically reduces the time spent on a fundamental, repetitive task.
Efficient and Detailed Routing: Automating branch routing saves significant time and ensures consistency and accuracy, including crucial wire sizing and voltage drop calculations that are essential for compliant and cost-effective designs.
Streamlined Workflow: From automated drawing preparation and schedule extraction upon upload to generating detailed Excel reports of quantities and PDF markups for download, Drawer AI guides you through a faster, more efficient process.
Why Choose Drawer AI?
Drawer AI is built specifically for electrical estimators to deliver tangible results:
Significant Time Savings: Users consistently report substantial reductions in takeoff time. Starr Electric Company, for example, saved 70% of their time on a single project by using Drawer AI to analyze over 2,600 fixtures and 3,400 power devices. This efficiency gain translates directly into the ability to bid on more projects or allocate time to other critical tasks.
Increased Accuracy and Reduced Risk: Automation powered by AI minimizes human error in counting and routing, leading to more accurate bids and reduced project risk. More time is available for you to analyze the estimate rather than just compile it.
Ease of Use and Review: The platform is designed to be intuitive, making it easy to upload drawings, review AI-generated results with QA tools, and download comprehensive reports.
Conclusion
Drawer AI provides electrical estimators with a powerful, accurate, and easy-to-use solution to significantly accelerate takeoff and estimating workflows. By automating manual tasks like quantification, routing, and stitching, it frees you from tedious work, allowing you to focus on analysis and winning bids.
More information on Drawer AI
Launched
2020-12
Pricing Model
Paid
Starting Price
$150 user/month
Global Rank
3624620
Follow
Month Visit
<5k
Tech used
Top 5 Countries
100%
United States
Traffic Sources
15.63%
1.02%
0.04%
5.05%
39.41%
38.85%
social
paidReferrals
mail
referrals
search
direct
Drawer AI was manually vetted by our editorial team and was first featured on 2025-06-24.
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