Deep Research in Few Minutes with Agent.ai

This is a submission for the Agent.ai Challenge: Full-Stack Agent (See Details)

What I Built

I built an AI agent that automates academic and market research by scraping data from the web, summarizing findings, and generating structured reports. This agent solves the problem of time-consuming manual research by aggregating and analyzing data from multiple sources (Google, YouTube, news articles) in minutes. Researchers, students, or professionals can use it to:

• Track trends in their field.
• Generate summaries of complex articles.
• Compile reports with actionable insights.

Demo

AI-Powered Research Assistant

Agent.ai Experience

It was a great experience so far. The drag-and-drop workflow builder made it easy to connect actions like Use GenAI and Call Serverless Function without coding making it accessible and easy to pick up.

My main challenge was using the serverless function. The variable handling and debugging variable mismatches (e.g., clean_text in serverless functions) required trial and error.

Conclusion

This project demonstrated how Agent.ai empowers users to build end-to-end AI workflows that solve real-world problems efficiently. By combining web scraping, GenAI summarization, and automated reporting, the Research Assistant reduces hours of manual work into minutes. While challenges like variable management tested my patience, the platform’s flexibility and AI integrations made the process rewarding.