The local-first control plane for AI agents.
From experiments to reliable work. Cerevisor is a local-first desktop harness for operators, founders, and teams. Build, run, and audit multi-agent workflows across any provider, and turn scattered AI experiments into repeatable, auditable work. Free to start, with a 7-day full Pro trial.
Adoption stalls where orchestration begins.
- One chat is not a workflow.
- Real work needs multiple agents, handoffs, and a shared context. Bolt those onto a chat UI and every team re-invents orchestration from scratch.
- No one trusts a black box.
- When an agent makes a decision in production, "we will look into it" does not fly. The harness logs every tool call, every approval, every model decision, so any run can be replayed on demand.
Latest Insights
- AI agent memory now ships with a retention policy. Your reviewers' memory does not.
- What survives when a multi-agent system architecture loses the app mid-run
- AI agent orchestration frameworks report success. Almost none of them define it.
- Alibaba Priced Its Biggest Open Model and Gave Away the One Teams Actually Run
- A Button That Lies Is Worse Than a Missing Feature
- The attention budget your AI agent orchestration plan is missing
- How to set up an MCP server for a real agent workflow
- A Private LLM Is a Claim Until You Audit It, and So Is Your AI Code Review
- A private LLM is an audit result, not a download: what still left the machine after we brought the model home
- AI code review does not get cheaper as the agent gets better
Stop wiring agents. Start running them.
Cerevisor is the desktop harness that turns multi-agent AI from a research project into something a small team can run, audit, and trust. Free to start. 7-day full Pro trial. No card.
- Portability first: Swap providers and harnesses without rewriting workflows.
- Local-first: Runs on the machine. Keys and data never reach Cerevisor.
- Audit-ready: Every run replayable from disk.