Swarm Orchestration

Multi-agent coordination is achieved by orchestrating swarms across dynamic topologies, allowing agents to execute parallel tasks with automatic distribution and shared memory state.

Multi-agent orchestration supports mesh, hierarchical, and adaptive topology patterns to distribute tasks dynamically and scale collaborative workflows across distributed agents.

Fault tolerance and load balancing for distributed AI workflows are managed through built-in task orchestration APIs that handle agent lifecycle management and redistribute tasks during failures.

Yes, you need agentic-flow to initialize a swarm, spawn agents, and manage their lifecycles through integrated task orchestration APIs and hooks.

Memory coordination across agents maintains shared state during task execution, enabling distributed agents to access and update collective memory throughout the workflow.