FactoryPilot

FactoryPilot is an AI copilot that combines factory knowledge and real-time data to drive smarter operational decisions.

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Inspiration

Manufacturing teams make hundreds of operational decisions every day, but the information they need is often scattered across inventory systems, spreadsheets, SOPs, and internal documentation. Finding the right answer can take longer than making the decision itself.

We wanted to build an AI copilot that gives factory operators and managers a single place to ask operational questions and receive answers grounded in both company knowledge and live inventory data.

What it does

FactoryPilot is an AI manufacturing copilot that combines organizational knowledge with real time inventory information.

Users can:

Ask natural-language questions about inventory, materials, and products. Check stock availability before scheduling production. Search manufacturing documentation and procedures. Receive context aware recommendations based on operational data. Access a single conversational interface instead of navigating multiple systems.

The goal is to reduce decision time and help factories operate more efficiently.

How we built it

FactoryPilot consists of four main components:

A FastAPI backend that orchestrates AI workflows. A React/Next.js frontend providing a conversational interface. A PostgreSQL database storing inventory and manufacturing information. An LLM integrated with a Retrieval-Augmented Generation (RAG) pipeline that combines internal documents with structured inventory data.

The application retrieves relevant manufacturing knowledge, fetches live operational information, and lets the language model generate responses grounded in both sources.

Challenges we ran into

One of the biggest challenges was combining structured data with unstructured documentation.

Inventory lives in relational databases, while procedures and manuals are text documents. Making the AI understand both sources simultaneously required designing a retrieval flow that keeps responses accurate and minimizes hallucinations.

Another challenge was keeping the system responsive while performing retrieval and AI inference.

Accomplishments that we're proud of

Built an end-to-end AI manufacturing assistant. Successfully combined structured inventory data with knowledge retrieval. Created a conversational interface that answers operational questions in natural language. Designed an architecture that can easily integrate with existing ERP systems.

What we learned

Throughout this project we learned that building AI applications goes beyond connecting an LLM.

The real challenge is designing reliable data pipelines, retrieval strategies, and system architecture so that answers are useful, trustworthy, and grounded in business data.

We also gained experience integrating modern AI tooling with traditional enterprise software.

What's next for FactoryPilot

Our vision is to evolve FactoryPilot into a complete AI operations platform for manufacturers.

Future improvements include:

Production planning assistance. Predictive inventory and stock forecasting. Supplier recommendations. Demand forecasting. Quality control insights. Voice interaction for factory floor operators. ERP integrations with SAP, Oracle, Microsoft Dynamics, and other manufacturing systems.

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