cognizant-ai-lab/neuro-san-studio
A playground for neuro-san
What it solves
Neuro SAN Studio simplifies the creation and deployment of complex multi-agent AI systems. It removes the need for extensive coding by allowing users to design agent networks through declarative configurations, solving the orchestration complexity that typically makes building collaborative AI systems slow and difficult.
How it works
It serves as a playground for the Neuro SAN framework, using HOCON configuration files to define how LLM-powered agents interact and delegate tasks. The system employs the AAOSA protocol for adaptive, decentralized communication and includes a specialized "Agent Network Designer" meta-agent that can automatically generate entire agent networks from natural language descriptions. It also features "Sly-Data" for secure data transfer between agents without exposing sensitive information to the LLMs.
Who it’s for
- ML Engineers and Developers prototyping production-ready agent networks.
- Researchers exploring adaptive AI systems.
- Domain Experts who want to configure AI agents for specific industry verticals (e.g., banking, insurance, telco) without writing code.
Highlights
- Declarative Design: Define entire networks via HOCON files rather than hard-coded logic.
- Automated Network Generation: A meta-agent that designs, links, and writes instructions for new agent networks based on user prompts.
- Broad Integration: Supports various LLM providers (OpenAI, Anthropic, Google Gemini, Ollama) and external tool ecosystems like CrewAI, LangChain, and MCP.
- Secure Data Handling: Uses Sly-Data to protect sensitive information during inter-agent communication.
- Interactive UI: Includes the nsflow UI for visualizing and testing agent networks.