Your company's knowledge is scattered across 15 tools. Nobody knows where anything is.

Slack for conversations. Google Drive for documents. Notion for the wiki. Gmail for client communication. Zoom for meetings. Linear for tickets. GitHub for code. Dropbox for assets. Each tool has its own search, and each search only covers what's inside that tool. The answer to "what did we decide about the pricing change" might be in any of them, or spread across three of them, and nobody has time to run the same query in eight different search bars.

Enterprise search tools exist. Most of them are built for companies with 1,000+ employees and cost accordingly. They take months to implement, require IT involvement, and produce results that look like a list of documents rather than an answer to a question. The mid-market team with 10-200 people doesn't need an enterprise deployment. They need one search bar that actually works.

One search bar. Cited answers. Every tool.

AI search connects to Slack, Google Drive, Dropbox, Notion, Gmail, and meeting tools. Ask a question and get a cited answer drawn from every connected source. Not a list of documents to click through. An answer, with links to the specific Slack message, document section, or meeting timestamp where the information lives.

The search works by meaning, not keyword. "What's our approach to enterprise security questionnaires" finds the relevant documentation even if nobody titled a document with those words. The search understands the question, not just the terms.

The AI assistant goes further: ask it to synthesise across sources, compare what different teams have said about a topic, or trace the history of a decision across meetings and Slack threads. It cites every source it draws from.

Self-writing docs that centralise the scattered knowledge

The longer-term solution isn't just better search. It's reducing the scatter. Self-writing docs produce centralised documentation from the distributed conversations and activity happening across your tools. The engineering docs that would prevent the Slack archaeology. The decision logs that would prevent the re-debates. The onboarding guides that would prevent the first-week interruptions.

Search solves the retrieval problem today. Self-writing docs reduce the problem over time.

Who this is for

Startups that have outgrown Slack search. Engineering teams where context is in code, docs, Slack, and meetings. Product teams that can't find the spec they wrote last quarter. Sales teams looking for the case study that was shared somewhere. Marketing teams searching for the approved copy. Any team that's tired of running the same search in five different tools.

For the team knowledge base approach, see team wiki. For the full set of connections, see marketplace.

Get started

Give your team one search bar for everything. Try Fabric free. See pricing for teams.

FAQs

What tools does Fabric connect to?

Slack, Google Drive, Dropbox, Notion, Gmail, and meeting tools. See connections for the full list.

Does the AI give answers or just links?

Answers. The AI assistant produces cited answers drawn from every connected source, not a list of documents to click through.

Does it search inside documents?

Yes. AI search reads inside every PDF, slide deck, email, transcript, spreadsheet, and document.

How is this different from enterprise search like Glean?

Fabric is built for mid-market teams (10-200 people) who need fast deployment without IT involvement. Self-writing docs and agents go beyond search to actively centralise knowledge. See Fabric vs Glean.

Does the search understand meaning, not just keywords?

Yes. AI search finds answers by meaning. "How do we handle enterprise security questionnaires" finds the relevant policy even if nobody titled a document with those exact words.

Can the AI trace the history of a decision across tools?

Yes. The AI assistant can follow a decision from the Slack discussion to the meeting where it was debated to the document where it was formalised, citing each source.

Do self-writing docs reduce the scatter over time?

Yes. Self-writing docs centralise knowledge from distributed conversations into maintained documentation. Search solves the retrieval problem today. Self-writing docs reduce the problem over time.

How long does setup take?

Connect your tools in minutes. No IT deployment, no configuration project, no months-long rollout. The search works across connected sources immediately.

Can agents surface answers proactively?

Yes. Agents can monitor Slack discussions and surface relevant context from the knowledge base before anyone has to search.

Is our data secure?

Yes. Fabric uses AES-256 encryption and is CASA Tier 2 compliant. Your data is never used to train AI models.