Saad Ullah
⬤ Unwind AI recently unveiled an open-source Deep Search system built on Google ADK and Gemini 3. The agents autonomously scan over 100 sources and compile findings into structured reports. The project is accessible through a one-command template clone or direct deployment via Agent Garden.
⬤ These Deep Search agents use recursive reasoning to plan research tasks, gather information, self-correct during the process, and validate data before final output. With Gemini 3 handling the reasoning layer, the framework shows how large AI models are becoming autonomous research assistants that manage complex information flows. The ability to scan multiple sources represents progress in scalable research automation, cutting down manual work for similar analytical tasks.
⬤ Making the system open-source lets developers inspect, modify, and expand it. Integration with Google ADK signals the industry's move toward modular agent architectures and plug-and-play development. Agent Garden deployment makes experimentation easier, showing that multi-agent systems are entering a more standardized and accessible phase.
⬤ The launch of these Deep Search agents reflects growing momentum in applied AI research automation. As Gemini 3-based frameworks gain adoption, the market is seeing rapid evolution in autonomous analysis, verification, and large-scale data synthesis. This development highlights how AI research tools may influence the next wave of productivity, competition, and innovation in tech.
Saad Ullah
