MataConnect DataAgent

An intelligent multi-agent system that finds, cleans, and curates global women’s communities, your one-stop archive for every women’s network in the world.

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Inspiration

Women’s communities exist everywhere, yet finding, joining, and connecting with them remains a real challenge. From Meetup groups to alumni clubs, vibrant networks for women are scattered across countless platforms and hidden behind search barriers. MataConnect DataAgent was inspired by the need to surface and unify these communities—making them accessible and visible for every woman, everywhere.

Our goal use intelligent agents build the world’s most comprehensive, living archive of women’s groups-supporting empowerment, growth, and connection.

What it does

MataConnect DataAgent is a multi-agent system that autonomously discovers, scrapes, cleans, and enriches data about women-focused communities from across the web.

Key components:

  • Scraper Agents: Specialized agents for each data source (e.g., Google, Eventbrite, Meetup, and more) that collect raw community data.
  • Enricher Agent: Processes and enriches this data removing duplicates, standardizing entries, and adding useful metadata.

The result:
A living, searchable archive where users can instantly discover women’s communities relevant to their interests, goals, and location, across the globe.

How it was built

  • Data Gathering Agents:
    Use custom scrapers to pull community data from public directories and search engines.

  • Data Cleaning & Enrichment Agent:
    Fetches saved data(by Data Gathering Agent), removes duplicates, standardizes formats, and enriches records with additional metadata.

  • MongoDb Atlas(hosted on google ):
    Stores structured, enriched records from the agents. The database is integrated with vector search, enabling fast, intelligent search capabilities directly from the user-facing frontend.

  • Frontend:
    A React-based UI demonstrating how users can easily search and explore the archive.

  • Backend:
    FastAPI web server that powers all backend logic, managing the retrieval and display of community data.

  • Search Engine:
    Integrated Vertex AI Search to power advanced, relevant, and lightning-fast community discovery.

Architecture Diagram

Agent Overview

System Overview

Challenges encountered

  • Data Quality:
    Online community information is often inconsistent, outdated, or incomplete, making data cleaning and validation complex.
  • Scraping Limitations:
    With limited time, we couldn’t integrate every planned data source.
  • Ethics & Privacy:
    We prioritized ethical scraping and ensured respect for platform terms and user privacy throughout development.

Accomplishments

  • Built a functional multi-agent pipeline capable of collecting and cleaning data from multiple sources automatically.
  • Created a unified, enriched database that makes community discovery seamless and impactful.
  • Demonstrated how AI agents can drive real social change—empowering women to find support and connection worldwide.
  • Designed the system to be scalable and extensible for future global growth.

What's next for MataConnect DataAgent

  • Expand Data Sources:
    Integrate more countries, platforms, and (with consent) private networks.
  • Smarter Enrichment:
    Leverage advanced NLP and categorization to improve data quality and matching.
  • Full App Integration:
    Seamlessly power MataConnect’s full-featured app, delivering advanced recommendations and insights to users worldwide.

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