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Kepos
Shared memory for teams and their AI agents
Most AI memory tools give one agent recall. Most team wikis give humans a shared doc. Kepos does both: multiple AI agents and humans read/write the same memory in real time, with git-backed version history — nothing silently overwritten — and self-enforcing learnings, where a correction recorded once gets automatically blocked from recurring. Memory that behaves like code, not a mutable blob.
Hey Product Hunt 👋
I'm Ansgar, one of the founders of Tiamat Labs.
We didn't build Kepos to launch a product.We built it because we were drowning in our own mess.
Between running paid media accounts for a handful of clients and building out several product ideas in parallel, everybody had Claude, Cursor, Codex, and half a dozen agent sessions running at once, and every single one of them forgot everything the second the session ended.
I'd re-explain the same campaign structure, the same client quirks, the same "no, we tried that in March and it didn't work" three times a week. My team had the same problem from the other side. Knowledge scattered across docs, Slack, and whoever happened to remember it.
So we built the thing we actually needed: one memory layer that both our AI agents and our team read from and write to.
Git-backed, so nothing silently overwrites anything and we can see exactly what changed. And the part I care about most: when we correct an agent once, that correction gets recorded and enforced going forward, instead of the same mistake showing up again in the next session.
We've been running on it internally for a while now across real client work. Not a demo, our actual day-to-day. Today's the first time it's public.
I'll be around all day. Happy to answer anything. Architecture, how the multi-agent piece actually works, what we got wrong the first three times we tried to build this.
Fire away.
Ansgar
About Kepos on Product Hunt
“Shared memory for teams and their AI agents”
Kepos was submitted on Product Hunt and earned 8 upvotes and 1 comments, placing #42 on the daily leaderboard. Most AI memory tools give one agent recall. Most team wikis give humans a shared doc. Kepos does both: multiple AI agents and humans read/write the same memory in real time, with git-backed version history — nothing silently overwritten — and self-enforcing learnings, where a correction recorded once gets automatically blocked from recurring. Memory that behaves like code, not a mutable blob.
On the analytics side, Kepos competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how Kepos performed against the three products that launched closest to it on the same day.
Who hunted Kepos ?
Kepos was hunted by Ansgar Holtmann. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Kepos including community comment highlights and product details, visit the product overview.
Ansgar Holtmann