Our unified context and state layer provides the foundation for building sophisticated agentic teams that maintain coherent state across complex operations. Built with scalability and reliability in mind, this platform transforms how AI agents work together on challenging tasks.

• Hierarchical Memory Architecture. Our platform employs a three-tiered memory system that manages information at appropriate persistence levels. Working memory handles immediate execution context, project memory maintains task history accessible to the entire team, and organizational memory preserves patterns and reusable knowledge across projects.
• Team-Oriented State Management. Your agent teams share information seamlessly through scoped context access configurable at global, team, and individual agent levels. Our real-time state synchronization with a pub/sub model ensures all agents work with current information, while built-in conflict resolution protocols maintain consistency during concurrent operations.
• Dynamic Team Formation. The system optimizes agent collaboration through role-based assignment, matching specialized agents to appropriate tasks. Performance monitoring tracks effectiveness to adjust team composition, while our director/worker model enables coordinating agents to manage specialized workers efficiently.

Our enterprise-grade execution system ensures reliability through transaction logging, process checkpointing, and priority-based resource allocation. This means your agent applications can handle interruptions gracefully and maintain performance during complex operations.

Seamless Integration

Connect with your existing tools and frameworks through our framework adapters for LangChain, AutoGen, and other popular systems. Our API-first design provides RESTful and GraphQL interfaces for all capabilities, while our asset store integration links vectorized document repositories directly to agent context for enhanced knowledge management.