ScalaCode partnered with an emerging construction technology company to build an AI-powered web-based SaaS platform that automates electrical takeoff and material estimation from residential electrical drawings. The goal was to eliminate manual symbol counting from electrical plans and enable electricians to generate accurate material lists and quoting inputs within minutes.
The platform was launched to address a major challenge in the construction industry: the time-consuming and error-prone process of manual electrical takeoff. Traditional estimation methods require electricians to manually interpret drawings, count symbols, and prepare material lists, often leading to delays and inconsistencies. The solution streamlines this workflow by using AI to automatically analyze electrical plans and generate accurate material estimates through a simple, web-based interface.
ScalaCode designed an intelligent, AI-driven solution that transforms complex electrical drawings into accurate, usable takeoff data with minimal manual effort.
Automated OCR processes electrical drawings to accurately extract legend definitions and textbased annotations, forming the foundation for reliable symbol interpretation.
Extracted legends are used to guide AI-powered computer vision models, ensuring electrical symbols are detected and classified based on drawing-specific context rather than generic assumptions.
A secondary AI reasoning layer handles complex layouts, overlapping annotations, and certification stamps, improving detection accuracy without requiring manual plan cleanup.
All detected symbols are overlaid directly on the plan, enabling electricians to visually validate results and make instant corrections where edge cases occur.
The platform supports dynamic subscription rules, allowing plan limits, feature access, and usage thresholds to be adjusted through configuration rather than code changes.
React.js, Tailwind CSS
Node.js, REST APIs
Google Vision API
Fine-tuned object detection models with OpenAI-assisted fallback
PostgreSQL
AWS (EC2, S3, CloudWatch)
Stripe Subscriptions
Git-based deployment pipelines
React
Tailwind
Node.js
Google Vision API
PostgreSQL
Amazon S3
Amazon CloudWatch
Amazon EC2
Stripe
Electrical drawings varied significantly across builders and architects, with no standardized legend formats. This inconsistency made it difficult to reliably interpret symbols using traditional rule-based detection methods.
Plans often contained rotated or mirrored symbols, overlapping annotations, certification stamps, and dense notes. These visual obstructions interfered with accurate symbol recognition and increased the risk of miscounts.
While automation was essential to reduce time and effort, electricians still required the ability to review and correct results. Achieving high AI accuracy without removing human validation was a critical challenge.
Processing large drawings with OCR and computer vision models introduced significant computational costs. The platform needed to scale efficiently while maintaining performance and controlling ongoing AI usage expenses.
Enables uploading and processing of multi-page electrical plans in PDF, PNG, and JPG formats.
Uses OCR and AI to detect legends and accurately map electrical symbols.
Identifies and counts lighting, power, fan, and data points with high accuracy.
Provides bounding boxes for detected symbols and allows manual edits to handle edge cases.
Generates structured takeoff reports available in PDF and CSV formats.
Offers Stripe-based tiered subscriptions with a mobile-friendly dashboard for electricians and contractors.
Everything we asked for was done quickly and efficiently. ScalaCode solved problems without delays or excuses.
Recognized by Industry Leaders & Valued by Global Clients
