🧠 AI Research Studio — Your AI Research Team

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

What if you could turn a research question into a structured report without hiring a research assistant, juggling multiple AI tools, or depending entirely on a proprietary AI API?

That question inspired AI Research Studio — an open-source, multi-agent AI research application built around open-weight models, local inference, and a deployable web experience.

Instead of treating AI as a single chatbot that answers a question and stops, AI Research Studio approaches research as a collaborative workflow. Specialized agents help search for information, analyze findings, write a report, and critique the result.

The idea is simple: make useful AI-powered research accessible to independent developers, students, creators, and small businesses — without making a closed AI service the only way the application can work.

AI Research Studio is a multi-agent research workspace that turns a topic into a structured research report.

Imagine you're a student investigating a new technology, a developer evaluating a framework, or a solo founder researching a market. You may have the question, but finding reliable information, organizing it, and turning it into something useful can take hours.

🤖 AI Research Studio brings those steps into one workflow.

Searches for relevant web information using tools such as Tavily and web-content extraction. The goal is to collect material that can inform the research.

2. Reader Agent — Turn information into insight

Analyzes retrieved content, identifies important findings, and helps separate useful information from the surrounding noise.

Organizes the findings into a readable, structured research document rather than leaving the user with a collection of disconnected AI responses.

4. Critic Agent — Challenge the first draft

Reviews the generated report and helps improve its clarity, relevance, and quality.

Together, these agents create a research pipeline that is more deliberate than a single prompt-and-response interaction.

AI Research Studio is designed around a real problem: research is valuable, but the process is time-consuming.

As a side hustle, the project could evolve into a hosted research assistant, a paid premium workspace, or a customizable research tool for small teams. Potential paid features include saved research histories, richer exports, configurable agent workflows, and team workspaces.

These are possible future business models, not existing paid features. The core project is intended to remain open for experimentation and community contributions.

https://atlas-ai-research-studio.onrender.com/

Open the app, enter a research topic, and explore the research workflow and generated output.

The project is hosted on Render so people can try the application through a browser instead of first installing a Python environment and configuring a local model.

Note: the hosted experience depends on the deployment configuration and availability of its connected services.

A multi-agent AI research system that transforms a research question into a structured, comprehensive report.

AI Research Studio is an open-source, multi-agent AI application designed to make research more accessible and efficient.

Instead of relying on a single AI response, the application organizes research into specialized stages. Agents collaborate to gather information, analyze relevant content, generate a report, and review the result.

Use a hosted LLM through Groq or run a compatible open-weight model locally using Ollama.

🎯 The goal: Turn a simple research topic into a useful, structured report with less manual effort.

Feature Description 🔎 Search Agent Finds relevant web information using the configured search tools. 📖 Reader Agent Processes retrieved content and extracts useful insights. ✍️ Writer Agent Organizes research into a readable …