Development of an Automated Grant Database for Subvention Prestige

The objective is to build a complete, autonomous, and user-friendly grant database focused on programs available in Quebec. This tool will help Subvention Prestige streamline its research process and better serve clients by eliminating the need for repetitive manual searches. The final system must be fully functional, automated, and designed for long-term use. Student Responsibilities Participants will be expected to: Analyze requirements and design a scalable, structured grant database. Develop automated web scraping scripts using Python (e.g., BeautifulSoup, Selenium, or APIs if available) to extract data from key public websites (e.g., Quebec government, Investissement Québec, Fundica, etc.). Integrate the scraped data into a functional and searchable database (e.g., Airtable, PostgreSQL, Google Sheets via API, etc.). Create a user interface that enables easy filtering and searching of grant programs by: Sector Eligibility criteria Funding amount Application deadline Set up a process for automated or semi-automated data updates (via cron job, GitHub Actions, or automation tools like Make/Zapier). Provide a clear user guide (written or video-based) to explain: How to maintain the system How to manually add or edit data if needed How to run or modify the scraping scripts Expected Deliverables A fully functional and connected grant database Scraping integration from 5 to 10 key sources A clean, searchable user interface Automated update system Clear documentation and maintenance guide Suggested Tools (not mandatory) Python (BeautifulSoup, Requests, Selenium, Scrapy) Airtable, PostgreSQL, Notion, or AppSheet Zapier or Make (Integromat) for automation GitHub for version control and task automation A fully autonomous and production-ready grant database, allowing Subvention Prestige to search, filter, update, and maintain Quebec grant listings without ongoing manual research or technical intervention.