MassGen Multi-Agent System

Example Use Cases

• 1

  Collaboratively solve complex tasks using multiple AI models and tools.

• 2

  Parallel processing and iterative refinement to improve solution quality.

• 3

  Real-time collaboration and consensus building among diverse AI agents.

Description

MassGen leverages multiple AI agents working in parallel to tackle the same problem, sharing insights and refining solutions collaboratively. It uses a consensus-based approach where agents vote on the best answer after iterative improvements, enabling continuous output enhancement. The system supports diverse AI models and tools, real-time collaboration, and live visualization through a textual user interface or web UI. This framework is designed to scale AI problem-solving by harnessing collective intelligence from multiple agents.