Ask most AI tools about something you told them last week and you get a pause, a database lookup, and a reply that sounds like a search result. Bourdon works the way human memory does: it recognizes you instantly, starts responding, and pulls the details up in the background. One memory, shared by all your agents. What you tell one, the others already know.
When you see a familiar face you don’t freeze while you search your memories. You know them first, and the details arrive while you’re already saying hello. Today’s AI does the opposite: silence, search, then a reply. Bourdon puts the steps back in human order: recognition first, hydration second, archive descent third.
human: speaks. human: speaks again. | | v v (silence, retrieval, search...) | | v v ai: replies. ai: replies.
Claude, Codex, Cursor, Copilot, and Devin write to and read from one shared, federated memory, so a fact learned by one is recognized by the rest, across accounts and machines. Your own agents join with a line of config. Gemini and Hermes adapters are on the way.
Three field tests on live agents against real work.
Self-hosting is the default and it is the whole engine, cross-agent federation included. Managed hosting is coming for teams that would rather not run a box. The free to paid line is operations, never engine capability: you pay for uptime, not for features.
Bourdon is one organ of a fleet instrument. Its sibling Positif is the cross-agent routing: what the fleet is allowed to do. Bourdon is the cross-agent memory: what the fleet knows. Tremulant is the conductor, for when the fleet acts on its own — and Prestant is the console in front of them all. Each with its own brand; one instrument.
The hosted console, new adapters, and releases, the moment they land. No noise, just Bourdon.
Building on agent memory, integrating an adapter, or reselling Bourdon? Tell us what you have in mind.