Classify Emails

About the project

Inspiration
The idea for Classify Emails came from the frustration of managing an overflowing inbox filled with emails from various categories. As emails pile up, it becomes increasingly difficult to prioritize important messages, respond in a timely manner, and organize everything without wasting valuable time. Inspired by the need for a more efficient, AI-driven solution to email management, I set out to build an app that could automate the sorting of emails and generate intelligent responses to ease the burden on users.

What I learned
Throughout the development of this project, I learned how to effectively integrate AI models, particularly for email classification, and how to handle email data securely using Google APIs. I gained hands-on experience in using the Gmail API, integrating OAuth for secure user authentication, and leveraging advanced AI models like Groq for categorizing emails. Additionally, I delved into using Sambanova’s API for enhanced functionality, which pushed my understanding of AI applications in real-world scenarios.

How I built the project
The project was built using Next.js 14, allowing for a fast and responsive frontend, combined with Tailwind CSS for the UI design. Google OAuth was implemented to authenticate users and securely fetch email data via the Gmail API. For the email classification, I utilized the Groq AI API and Sambanova API, using them to categorize emails into meaningful groups like Promotions, Social, and Spam. Each email snippet is then classified using powerful AI models, and smart AI-generated responses are provided for easy replies.

Challenges faced
One of the main challenges was understanding how to effectively fetch and parse emails from the Gmail API, especially handling various email formats. Integrating AI for accurate classification was another challenge, as it required fine-tuning and testing the models to ensure that they could classify emails correctly across different categories. The seamless integration of AI for generating responses posed a significant challenge, particularly ensuring the responses were accurate, professional, and appropriate for various email types. Additionally, security was a major concern, as it involved handling sensitive user data and making sure it was protected.

Built With

• gmail-api-apis:-groq-ai
• gmailapi
• googleoauth
• next.js14
• tailwind-css-cloud-services:-google-oauth