ConstructCopilot AI

• 

  Working

• 

  Introduction

Inspiration

In the construction world, time is money, and information is often buried deep inside lengthy reports, blueprints, and permits. We were inspired by the frustration that site engineers and project managers face when trying to extract quick answers from massive project documentation. We thought: what if there was an AI assistant that could answer any question about any construction document — instantly?

That’s how ConstructCopilot AI was born — a smart, searchable copilot for your construction documents.

What It Does

ConstructCopilot AI allows users to:

• 📤 Upload project documents (PDF, TXT)
• 🤖 Ask natural language questions about them
• ⚡ Receive instant answers powered by Google's Gemini API
• 🔐 Store documents securely with Firebase

It’s like having a site-savvy AI assistant that works 24/7 and understands your docs like a pro.

How We Built It

• We built a clean, responsive frontend using Streamlit.
• Integrated Google Gemini API for natural language understanding and response generation.
• Used Firebase Storage to store uploaded documents securely.
• Embedded simple RAG (Retrieval-Augmented Generation) logic to connect user queries with file content.

Challenges We Faced

• Getting the free-tier Gemini API to handle document-level context.
• Efficiently parsing and cleaning text from PDFs.
• Managing Firebase authentication and storage in a simple but secure way.
• Making the UX clean and fast enough for real-world construction workflows.

What We Learned

• Building GenAI apps doesn’t require big infrastructure — just smart integration.
• Even simple AI tools can create huge value in industries like construction.
• Firebase + Gemini is a powerful stack for fast, free MVPs.

Built With

• 🐍 Python
• 🎈 Streamlit
• 🔥 Firebase (Auth + Storage)
• 🧠 Google Gemini API
• 📄 PyMuPDF (for PDF parsing)
• 🛠 LangChain (lightweight retrieval logic)

Built With

• firebase
• gemini
• langchain
• python
• streamlit