MeshFlow: Agent Orchestration Released

MeshFlow has been unveiled, designed to solve the regulatory compliance, cost management, and failure recovery challenges faced when adopting AI agents for enterprise use. The core of this framework is handling governance at the infrastructure level rather than as middleware.

Key Technical Features:

• 15-Stage Kernel System: Every agent step goes through a fixed 15-stage process that includes identity verification, rate limiting, budget enforcement, PII detection, risk classification, and audit logging.

• Token Cost Optimization (70-85% reduction):

  • cache_control: Applies caching to system prompts and tool definitions.
  • ModelRouter: Automatically routes to lightweight models based on task type.
  • ContextCompactor: Sliding window summarization based on token thresholds.
  • RAGTokenBudget: Sets token caps and applies strategic truncation during knowledge injection.
  • ContextDeduplicator: Deduplicates shared context across parallel agents.

• SHA-256 Audit Chain: Each step's record is stored in a chain structure that includes the hash of the previous record, providing security that enables immediate detection of log tampering.