EXTRACT · GOVERN · SERVE · REPLAYABLE · COMPOUNDING
What Memoth is
Typed fragments, not chunks — what a mind would keep.
Every memory carries its source; every change hits a ledger.
What agents learn writes back. Week two beats week one.
The problem
Bolt-on retrieval and search indexes both miss what a mind does with knowledge. Watch two agents fail the same way.
Bolt a vector store onto an agent and every prompt gets stuffed with half-relevant snippets, or the agent starts cold with nothing at all. Either way it burns tokens re-deriving what your org already knows, and hallucinates from the noise.
Your company's knowledge lives in wikis, tickets, chats and meeting notes. Search makes it findable. But nobody extracts it the way a mind does: the facts, the patterns, the resources, the procedures. So agents query documents instead of remembering anything, and nothing they learn ever flows back.
Two agents, two domains, one failure mode. Every answer came back verbatim from the org's own docs. None of them flagged a conflict.
The loop
Click a card to bring it forward
Memory types
Incidents, decisions, the demo that failed and why. The events your org would rather not relive twice.
Facts, ownership, configs, the current state of the world. Updated when the world changes, never silently lost.
Runbooks, sequences, the steps that worked last time. What agents learn on the job lands here.
The slice served into the agent's context for this task: persona-fit, domain-fit, task-fit. This is the one your agent actually feels.
The split that matters: episodic, semantic and procedural memory get extracted into the store. Working memory is what gets served, per agent, per task.
Measured, not promised
Results from our evaluation suites. We run the same suites on your corpus during a pilot and hand you the table.
Plug in
Reads from Notion, GitHub, Granola, Document upload, Confluence, Jira, Slack, Google Drive, Google Docs, Linear. Serves Claude, ChatGPT, Cursor, OpenClaw, Hermes, NemoClaw, Your own platform, Self-hosted.
Design partners
The memory layer under your agents early, tuned to your domain first. We measure token cost, task success and served-stale rate, and hand you the numbers. If they don't show up, you walk with a free audit.
Founder-direct iteration. Your corpus never leaves your environment.