FLEECE / AI BRAINYour team already answered this. Twice.
The best answer to most tickets was written months ago by someone who has since moved teams. It is sitting in a resolved Zendesk ticket, an Intercom conversation, or a Slack thread with engineering — none of which your help centre or your AI assistant can reach.
Fleece AI Brain gives support teams one searchable memory of every answer they have already given: it syncs Zendesk, Intercom, Confluence, Notion, Slack and Jira into a local-first knowledge graph on your own machines, then serves it to Claude and any MCP-compatible assistant. Resolved tickets stop being an archive and start being a source.
Resolved is not the same as remembered
Support generates more written knowledge per week than any other function, and files almost all of it where nobody will look again. A ticket closes and its reasoning is archived. The macro library covers the common cases and none of the hard ones. The help centre lags behind the product by a release or two.
The result is a team that solves the same hard problem repeatedly, at wildly different speeds depending on who picks up the ticket. And when an AI assistant is put in front of that mess, it drafts confident replies from the help centre alone — which is exactly the subset that is most likely to be out of date.
- A tricky integration error gets re-diagnosed from scratch because the last fix lives in a closed ticket.
- Two agents send different answers to the same question in the same week.
- The workaround engineering posted in Slack never reaches the people answering tickets about it.
- An AI draft cites a help-centre article that was superseded by a release two months ago.
Turn resolved tickets into the knowledge base
The Brain syncs your support surfaces into one typed graph: conversations from Zendesk and Intercom, internal documentation from Confluence and Notion, the Slack channels where escalations get worked, and the Jira issues behind known bugs. Each becomes a Markdown note with links, so a recurring problem accumulates its own history — symptom, diagnosis, fix, and the ticket that proved it.
Exposed over MCP, that graph is what your AI assistant reads before drafting. Answers cite the ticket or the thread that established them, which makes them checkable rather than merely fluent. And because the vault is plain files on your own machines, customer conversation content is not being copied into a third-party index — usually the first question your DPO asks.
The connectors support teams start with
One sign-in each from the desktop app; every connector page states exactly what it syncs.
Zendesk
Connect Zendesk to Fleece AI Brain: every support ticket becomes a note in a local-first knowledge base your AI queries over MCP.
See what it syncs →Intercom
Connect Intercom to Fleece AI Brain: every customer conversation becomes a note in a local-first knowledge base your AI queries over MCP.
See what it syncs →Confluence
Connect Confluence to Fleece AI Brain: every page becomes a note in a local-first knowledge base your AI apps query over MCP. Sign in once.
See what it syncs →Notion
Connect Notion to Fleece AI Brain: every workspace page becomes a note in a local-first knowledge base your AI apps query over MCP. Sign in once.
See what it syncs →Slack
Connect Slack to Fleece AI Brain: every channel message becomes a note in a local-first knowledge base your AI apps query over MCP. Sign in once, sync in the background.
See what it syncs →Jira
Connect Jira to Fleece AI Brain: every issue, description and status becomes a note in a local-first knowledge base your AI apps query over MCP.
See what it syncs →What support leaders weigh this against
Support shortlists are usually a knowledge-verification tool or an enterprise search layer bolted over the helpdesk.
Worth reading first
Background support leads tend to want before running a trial.
The 8 Best AI Memory Tools for Teams in 2026
We've run our own agents against every serious option on the market, and the pattern is clear: teams need memory that persists, that a whole fleet of AI apps can read, and that doesn't scatter your knowledge across a dozen clouds. Here are the eight AI memory tools we'd actually recommend in 2026, ranked and compared.
Obsidian for Teams in 2026: What Works, What Breaks
Obsidian is the best personal knowledge tool we've ever used, and for a small, trusted team a shared vault genuinely works. At team scale it breaks in predictable places: no per-person permissions, concurrent-edit conflicts, no admin view, and no shared memory your AI agents and connectors can feed. Our verdict: keep Obsidian for personal thinking, and add a team brain that speaks the same plain Markdown — which is exactly what Fleece AI Brain is — once more than a handful of people and agents depend on the same knowledge.
Shared Memory for AI Agents with MCP: One Brain, Queried by All of Them
Your AI agents each have their own amnesia. Shared memory for AI agents with MCP fixes that — one long-term brain that Claude, Cursor, Cline and your custom agents all read and write. Here's why it matters and how to build it.
How a support team starts
- 01
Connect the helpdesk first
Zendesk or Intercom is where the answers already are. Syncing it turns a closed-ticket archive into a body of knowledge the rest of the graph can link to.
- 02
Add the docs and the escalation channels
Confluence or Notion for the official version, Slack and Jira for the unofficial one — the workaround, the known bug, the fix that has not shipped yet.
- 03
Draft with the graph, not the help centre
Point your assistant at the Brain over MCP so replies are drafted from what the team has actually resolved, with the ticket cited. Verify the citation before sending; that habit is what keeps the quality high.
- 04
Let Janitor keep it clean
Support knowledge duplicates fast. The Janitor scan proposes merges and archives so near-identical notes collapse into one, and on Teams the autopilot applies them unattended.
Support questions
Does this replace Zendesk or Intercom?
No. Your helpdesk stays the place tickets are worked and measured. The Brain syncs from it so that resolved conversations become part of a graph your AI tools can query — the layer helpdesks were never designed to provide.
Is this just a smarter macro library?
Macros answer the questions you predicted. The graph answers the ones you did not, because it is built from what your team actually resolved, linked to the bug or the release that caused it. Macros stay useful for volume; the graph covers the long tail.
Does customer conversation content leave our machines?
No. Connector content travels from the provider straight to your device, and the vault is a folder of Markdown files with a local SQLite index on your own disk. Sync between your own machines is opt-in and end-to-end encrypted.
How do we stop the AI from citing outdated answers?
Two ways. Answers carry provenance, so an agent sees the date and source before sending. And the Janitor scan surfaces duplicates and stale notes for merge or archive, so the graph converges on one current answer instead of accumulating three contradictory ones.
Can agents have different access levels?
On the Teams plan, yes — shared vaults with role-based access control, an audit log, and SSO through Google or Microsoft. Solo and Pro are designed for individuals and small teams on a single vault.
How much does it cost for a support team?
Teams is €49 per user per month and is the plan built for shared vaults and access control. Solo is €12 and Pro €24 for individuals and small teams. Every plan starts with a 14-day trial, cancel anytime.
Other teams
Answer once. Reuse it forever.
Connect your helpdesk during the trial, then ask about the error your team is tired of explaining.