Mail Marvel: An AI-Powered Email Classification and Scheduling Tool

Inspiration

In our increasingly digital world, email communication is essential, yet the sheer volume of messages can be overwhelming. Important emails often get lost in a sea of less relevant ones, leading to missed opportunities. This inspired us to create Mail Marvel, a tool that uses AI to filter and classify emails, ensuring users can focus on what truly matters.

What it does

Mail Marvel automatically classifies emails into categories like Important, Events, Pending Actions, and Job Searches. It also organizes emails into a schedule, allowing users to prioritize their time and manage their tasks efficiently.

How we built it

• Tech Stack:
  • Backend: Python, Langchain, Google API (Gmail)
  • Frontend: Streamlit for user interface, Plotly for visualizations
  • AI Model: Utilized OpenAI’s GPT for natural language processing and email classification
• Development Steps:
  1. Authentication: Implemented OAuth 2.0 for secure access to Gmail accounts.
  2. Email Retrieval: Developed functions to fetch and manage emails using the Gmail API.
  3. Classification Logic: Built an AI model to categorize emails based on content, ensuring users receive prioritized notifications.
  4. User Interface: Designed a user-friendly interface in Streamlit to display classified emails and upcoming schedules.

Challenges we ran into

• API Limitations: Navigating the Gmail API's restrictions and quotas posed initial challenges in efficiently retrieving email data.
• Date Parsing Issues: Ensuring accurate date formats and handling various input formats required robust validation.
• User Experience Design: Balancing functionality with aesthetics to provide a seamless user experience in the Streamlit app took several iterations.

Accomplishments that we're proud of

• Successfully implemented a functional prototype that accurately classifies and schedules emails.
• Enhanced the user interface, making it intuitive and responsive.
• Received positive feedback from initial users on the effectiveness of the email filtering process.

What we learned

• Gained hands-on experience with Gmail API integrations and OAuth 2.0 authentication.
• Deepened our understanding of natural language processing techniques for real-world applications.
• Improved our skills in frontend development, particularly in creating engaging user interfaces using Streamlit.

What's next for Mail Marvel

• Feature Expansion: Plan to add more sophisticated filtering options and user-customizable settings.
• Mobile Accessibility: Explore developing a mobile version to increase accessibility.
• User Feedback: Continuously gather user feedback to enhance functionality and user experience.

Built With

• api
• cloud
• gmail
• google
• javascript
• javascript-frameworks:-frontend:-streamlit-for-building-the-user-interface-backend:-flask-(if-applicable)-or-any-other-relevant-framework-cloud-services:-google-cloud-platform-(for-hosting-services
• langchain
• openai
• pandas
• platform
• plotly
• postgresql
• python
• sqlite
• streamlit