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Rivet

Rivet

Rivet Actors: Durable, collaborative infrastructure for serious AI agents.

Rivet provides stateful actors and agent runtimes that keep context, persistence, and networking together for AI agents, workflows, and collaborative experiences, running on your existing infrastructure with global edge performance and built-in observability.
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Rivet is a stateful compute primitive designed for AI agents, collaborative applications, and long-running workflows that need durable execution without infrastructure complexity. Each Rivet Actor encapsulates in-memory state, persistence, networking, and scheduling so your agents and background jobs can maintain context indefinitely while scaling from zero to global traffic.

With Rivet, you get composable stateful workloads that plug into your existing stack—serverless, containers, or bare metal—while running close to users on a global edge network. Actors support in-memory state with SQLite persistence, automatic hibernation when idle, and instant wake-ups for bursty workloads. Built-in capabilities such as WebSockets streaming, durable queues, workflows with automatic retries, and cron-style scheduling make it easy to implement chat agents, multiplayer collaboration, and per-tenant backends.

For richer agent environments, agentOS adds a lightweight runtime with a real file system, V8 isolates, and configurable security policies. You can mount S3, SQLite, Google Drive, or host file systems, then expose your own APIs and tools through a unified interface that works with Claude Code, Codex, OpenCode, and other LLMs.

Rivet also ships with RivetKit and built-in observability: a SQLite viewer, workflow state inspector, real-time event monitoring, and an interactive REPL to debug actors in production-like conditions. This lets development teams start locally, validate behavior, and confidently scale to millions of concurrent actors without rewriting their architecture.

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