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AI assistant for analysis
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AI assistant on extracting delivery order
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dashboard
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Inventory list
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Login page
RicePilot AI
Inspiration
Rice is one of the most important agricultural products in Tanzania and across East Africa. During visits to warehouses and discussions with warehouse staff, I observed that many inventory operations still rely on handwritten delivery notes and manual data entry into spreadsheets. This process is slow, repetitive, and prone to human error.
I wanted to build a solution that combines artificial intelligence with warehouse management to simplify inventory operations, improve accuracy, and reduce the time required to process deliveries.
Demo Account Credentials: Email: admin@ricepilot.co.tz Password: RicePilot@2026! Link: https://ricepilot-ai-production-ycnpxx.laravel.cloud/
What it does
RicePilot AI is an AI-powered inventory management system designed specifically for rice warehouses.
The application allows warehouse staff to:
- Manage warehouses, suppliers, and products.
- Record stock-in and stock-out transactions.
- Upload delivery notes.
- Automatically extract structured information from delivery documents using OpenAI.
- Review AI-generated results before saving them.
- Keep inventory records accurate and up to date.
Instead of manually typing every product and quantity, the AI reads the document and prepares inventory information in seconds.
How we built it
RicePilot AI was built using:
- Laravel 12
- PHP
- MySQL
- Blade
- OpenAI API (GPT-5.6)
- Laravel Cloud for deployment
The application follows a modular architecture with separate components for inventory management, supplier management, warehouse management, document processing, and AI integration.
The OpenAI API analyzes uploaded delivery notes and converts unstructured text into structured inventory data that can be reviewed before being stored in the database.
Challenges we ran into
Several challenges came up during development:
- Designing reliable prompts that consistently extract structured information from different delivery note formats.
- Handling API configuration and deployment to a production environment.
- Managing environment variables securely while deploying on Laravel Cloud.
- Ensuring the extracted information is validated before updating inventory records.
- Completing a functional MVP within the limited Build Week timeframe.
Each challenge helped improve both the application architecture and the overall user experience.
Accomplishments that we're proud of
- Successfully built a working AI-powered warehouse management application.
- Integrated OpenAI GPT-5.6 to automate document understanding.
- Deployed the application on Laravel Cloud.
- Created an intuitive workflow for AI-assisted inventory processing.
- Delivered a solution focused on solving a real agricultural problem in East Africa.
What we learned
This project provided valuable experience with:
- Prompt engineering for structured document extraction.
- Building AI-assisted business workflows.
- Laravel Cloud deployment.
- Production environment configuration.
- Designing AI features that assist users while keeping them in control through human review.
Most importantly, I learned that AI creates the greatest value when it augments existing business processes rather than replacing human decision-making.
What's next for RicePilot AI
The vision for RicePilot AI extends beyond inventory management.
Future features include:
- Barcode and QR code support.
- OCR for scanned delivery notes and invoices.
- Inventory forecasting using historical stock movements.
- Multi-warehouse synchronization.
- Mobile application for warehouse staff.
- Analytics dashboards for business insights.
- Integration with accounting and ERP systems.
- Support for additional agricultural commodities beyond rice.
The long-term goal is to provide an intelligent warehouse management platform that supports agricultural businesses across Tanzania and the rest of East Africa.
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