Agent
Orchestration.
LLMs are stateless. Agents need durability. Rivet Actors provide the persistent memory and orchestration logic required to build autonomous AI systems.
Build Agents with Actors
Actors provide long-running processes, in-memory context, and realtime/native protocols for building stateful AI agents.
Why Actors for Agents?
Rivet Actors are the fundamental building blocks for agents that need to reason about state over time.
Long-Running Tasks
Agents can 'hibernate' while waiting for external API callbacks or human approval, consuming zero resources.
Realtime
Stream responses and updates in real-time via WebSockets. Agents can broadcast events, progress updates, and intermediate results as they work.
Durable Execution
Actors persist their thought process. If the server restarts, the agent resumes exactly where it left off, mid-thought.
Orchestration
Communicate between agents using low-latency RPC. Agents can 'hand off' state to each other effortlessly. Auto-scaling ensures optimal resource allocation as workloads grow.
Autonomous Coding Agent
Enable agents to operate directly on codebases with real-time feedback loops and durable process context.
- Real-time Monitoring: Stream shell outputs and linter results directly to the user interface.
- Durable Tool Loops: Agents can execute complex bash scripts and resume if the task is interrupted.
- Context Retention: Long-term memory of project structure, preventing repetitive discovery steps.
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Integrates with
Build smarter agents.
Give your AI the stateful foundation it needs to actually solve complex problems.