Multi-agent orchestration

Multi-agent orchestration

Run multiple AI agents in parallel or in sequence. Define handoff rules, share context, and coordinate complex workflows — without writing orchestration boilerplate.

Persistent memory

Persistent memory

Agents remember. Store structured facts, conversation history, or arbitrary embeddings in lloopback's memory layer and retrieve them semantically at query time.

Provider flexibility

Provider flexibility

Swap LLM providers without rewriting agent logic. Configure model, temperature, and cost caps per agent.

Channels and routing

Channels and routing

Route messages between agents, users, and external systems through named channels. Fanout, filtering, and priority queuing built in.

Task history and replay

Task history and replay

Every agent invocation is a first-class task with structured inputs, outputs, status, and timing. Replay tasks for debugging or regression testing.

Tool registry

Tool registry

Register tools once, use them across agents. Define JSON-Schema-backed function signatures, point to your backend, and lloopback handles invocation and error handling.

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