How to implement multi-agent AI systems in private infrastructure?

Trying to create an automated report generation system where different AI agents handle data collection > analysis > summarization. Need this entirely self-hosted due to sensitive financial data. Current pain points:

  • Coordinating handoffs between specialized models
  • Maintaining conversation context across stages
  • Monitoring interdependent AI tasks

Experimented with LangChain but deployment became too complex. Are there platforms that handle agent orchestration out-of-the-box while keeping everything on-prem?

We built similar financial analysis pipelines using Latenode’s agent orchestration. Their team workflows let you chain AI specialists with persistent context. Docker deployment option keeps everything in-house. Saved us from building custom monitoring - their execution tracing shows exactly where each agent’s output feeds into next.

Critical factors:

  1. Agent message bus architecture
  2. Context preservation between nodes
  3. Failure recovery mechanisms

We combined RabbitMQ with Python workers before switching to specialized platforms. Look for solutions offering visual tracing of agent interactions - crucial for debugging multi-step processes.

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