Many people struggle to find and apply for government welfare schemes because official websites are often confusing and require multiple steps. I wanted to build something that simplifies this entire process, especially for users in rural areas who may not be familiar with technology. This inspired me to create an automated assistant that handles everything from eligibility to application tracking.
What it does
SchemeFinder Pro is a web application that helps users:
- Enter their personal details once
- Receive suggested government schemes they are eligible for
- Submit the application automatically
- Get an instant email confirmation with all details
- Track the status of their application with a unique ID
It takes the burden off the user by automating repetitive tasks and simplifying the user experience.
How we built it
I built the project using:
- Python (Flask) for backend API and form handling
- HTML & CSS for frontend UI
- n8n for workflow automation
- Gmail API for sending automated emails
- Replit for hosting and deployment
The Flask server collects form data and sends it to an n8n webhook. n8n then automates sending confirmation emails and triggers other actions in the workflow.
Repo: https://github.com/diwakar142008/AI-scheme--assistant
Challenges we ran into
- Learning how to connect Flask with external automation tools like n8n
- Debugging webhook test vs production URLs
- Making sure the automation was reliable and triggered only when needed
- Formatting email content dynamically
- Deploying the app so that it can be accessed publicly
Accomplishments that we’re proud of
- Successfully integrated backend and automation workflows
- Built a working end-to-end product that accepts applications
- Automated email notifications with real user data
- Unique application ID generation for tracking
- Successfully deployed a live prototype (Replit)
What we learned
Through this project I learned:
- How to build REST APIs with Flask
- How webhook automation works with n8n
- How to handle and debug real API errors
- How to send structured emails using automation
- Deployment of Python apps on modern cloud platforms
What’s next for SchemeFinder Pro
In the future I plan to:
- Add AI eligibility prediction to match users with relevant schemes
- Support multi-language forms for wider reach
- Add SMS and WhatsApp notifications
- Create an admin dashboard to review applications
- Integrate with real government scheme databases
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