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Cover image for EstiForge: Building an Open-Source AI Engineering Estimation Assistant
Rittik Chakraborty
Rittik Chakraborty

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EstiForge: Building an Open-Source AI Engineering Estimation Assistant

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

EstiForge: Open-Source AI for Engineering Estimation

What I Built

EstiForge is an AI-assisted engineering estimation platform designed for independent engineers and small contractors.

The goal is to simplify the process of turning project requirements into structured estimates, Bills of Quantities (BOQs), and professional quotations.

Instead of manually preparing every estimate from scratch, users can describe their requirements, review the extracted inputs, calculate quantities, manage material and labour rates, and generate quotations.

I'm starting with electrical estimation, with a modular architecture that can expand to civil engineering and other trades.

Demo

Live Demo: EstiForge — Live Application

Code

GitHub Repository: EstiForge

How I Built It

EstiForge is designed around open-source AI and a modular architecture.

  • Next.js + TypeScript: Application framework and type-safe business logic.
  • Tailwind CSS + shadcn/ui: Responsive interface and reusable components.
  • llama.cpp: Local inference using compatible open-weight language models.
  • MongoDB: Persistent project, estimate, and quotation data.
  • Formula Registry: A modular approach to engineering calculations, with deterministic code for supported formulas.
  • Voice Input: Planned local speech recognition using Whisper through whisper.cpp.

The LLM helps interpret natural-language requirements and extract structured inputs. Engineering calculations and final pricing are handled separately so that model-generated text cannot silently determine the final estimate.

Why Does Open Innovation Matter?

Engineering projects can contain sensitive customer information, project specifications, and commercial rates.

Open-weight models and local inference offer the possibility of processing that information without sending every request to a third-party AI provider. They also give developers the freedom to change models, inspect their behaviour, and adapt the application to specific workflows.

Using open-source tools makes it possible to build a flexible estimation platform without depending entirely on proprietary AI APIs or their pricing.

My long-term goal is to make practical AI-assisted engineering tools more accessible to independent professionals and small businesses.

Prize Categories

  • Open-Source AI
  • Side Hustle

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