Private beta memodis is in private beta — onboarding a small group of pilot teams. Apply for access →
The memory layer · public beta soon

Knowledge that remembers itself —
for teams, and the agents they work with.

memodis captures every decision, doc, and conversation, then resurfaces the exact piece of context the moment a human or an AI agent needs it. No more re-asking. No more re-discovering. No more losing knowledge when people leave.

For teamsCapture · retrieve · share
For agentsContext API · MCP-native
Hosted in EUGDPR-first, SOC 2 in progress
◆ What is memodis

Every team has a graph of knowledge they never wrote down.

memodis watches the surfaces where work actually happens — docs, chat, calls, code reviews — extracts the decisions and facts, and stores them as a structured knowledge graph anyone (or anything) can query.

Knowledge graph, not a wiki

Facts, decisions, and people are stored as connected nodes. Ask "why did we pick Postgres?" and you get the original thread, the decision doc, and the engineer who made the call.

Semantic retrieval

Ask in natural language. memodis searches across embeddings, exact text, and graph paths simultaneously — and ranks by how recently the source was edited and how authoritative the author is.

Agent-ready context API

Every retrieval is also exposed as an MCP tool. Drop memodis into Claude, Cursor, your custom agents — they pull the same canonical context your team relies on.

Memory traces

Every answer comes with a trace — the underlying messages, the chain of references, the timestamp. Citations, not hallucinations. Reliable enough that compliance teams can use it.

Sources you control

Connect Slack, Notion, Google Drive, GitHub, Linear, Zoom — or pipe in your own. memodis indexes; the original sources stay where they are. Disconnect any time.

EU-hosted, GDPR-first

All data is stored and processed in the EU. Customer-managed encryption keys, full data export, granular deletion controls. SOC 2 Type II audit underway.

◆ Who memodis is for

Built for two kinds of memory loss.

Companies

When the person who knew leaves — and takes the project with them.

Series A through 500-person orgs lose 20–40% of their institutional knowledge to turnover, async sprawl, and silent doc decay. memodis catches it before it walks out the door.

  • Onboarding that doesn't take 3 weeks of pairing
  • Decisions you can audit two years later, with the original thread
  • One canonical answer instead of three contradictory wikis
  • Cross-team retrieval without permission spaghetti
AI agents

When your agent has the model — but none of the context.

An agent without your team's memory is a smart intern on day one. memodis plugs into MCP, LangGraph, Mastra, custom orchestrators — so the agent reads the same room your team does.

  • Tool-use endpoints for retrieval, lookup, and trace
  • Stable IDs for entities so multi-step agents don't get lost
  • Audit log of every agent query — who asked what, when, on whose behalf
  • Self-hosted option for regulated environments
◆ How it works

Three steps from messy to retrievable.

Step 01

Connect your sources

OAuth into Slack, Notion, Drive, GitHub, Linear, Zoom transcripts — or use the ingest API. memodis indexes incrementally; original docs stay where they are.

Step 02

memodis builds the graph

Decisions, entities, projects, people, and the edges between them are extracted with cited sources. You can review and correct anything that's wrong.

Step 03

Ask in chat or wire in your agent

Search the graph through the web app, the Slack bot, or the MCP server. Every answer carries the trace back to the source.

Private beta · pilot program

Apply to be one of our pilot teams.

We onboard a handful of companies each week. Tell us a bit about your team — we reply within 48 hours.

You're on the list.

We'll be in touch within 48 hours from hello@memodis.com. Watch the spam folder just in case.