Your sales team keeps pinging engineering for answers they should already have.

"How does our SSO implementation work?" "Can the platform handle 50,000 concurrent users?" "What's our data residency story?" "Does the API support webhook callbacks?" Every ping pulls an engineer out of flow state. The answers exist somewhere: in documentation, in Slack threads, in past sales conversations where the same question was answered. But the sales rep can't find them, so they ask the person who knows, and the person who knows loses thirty minutes of productive context.

Multiply by a dozen questions a week across a growing sales team and the engineering cost is substantial. It's not a sales problem. It's a knowledge retrieval problem.

A sales knowledge base that writes itself from real conversations

Self-writing docs produce a sales knowledge base from your team's actual conversations. When an engineer answers a technical question in Slack, the answer becomes part of the searchable knowledge base. When a sales call covers a technical objection, the transcript is searchable. The knowledge base builds itself from how the team already communicates.

Objection handling, competitive intel, technical answers, pricing precedents, and product capabilities, all assembled from real conversations rather than a battlecard someone wrote last year and forgot to update.

AI search so sales finds the answer before asking

AI search lets any sales rep ask "does our API support webhook callbacks" and get a cited answer from documentation, Slack, and past call transcripts. The AI assistant synthesises across sources. The answer is there. The rep just needed a way to find it.

The effect is cumulative. As more questions get answered in Slack, more call transcripts accumulate, and more documentation is produced, the knowledge base deepens. The rate of engineering interruptions drops because the answers become findable.

Agents that brief and draft

Agents assemble pre-call briefs from the account's history, competitive intel, and relevant technical documentation. They draft follow-up emails from call transcripts. They flag when a new question appears that isn't covered by the existing knowledge base. The operational overhead around each deal shrinks.

Who this is for

Sales teams that depend on engineering for technical answers. Engineering teams tired of being interrupted by sales. Startups where the founder handles both roles and needs the knowledge captured for the first sales hires. Product teams producing product knowledge that sales needs access to.

For the full sales knowledge workflow, see Fabric for sales teams. For individual reps, see Fabric for sales.

Get started

Build a sales knowledge base that stops the pings. Try Fabric free. See pricing for teams.

FAQs

Does the sales knowledge base write itself?

Yes. Self-writing docs produce a sales knowledge base from Slack, meetings, and call transcripts. No manual content creation.

Can sales reps search for technical answers without asking engineering?

Yes. AI search finds cited answers from documentation, past conversations, and meeting transcripts. The answer that used to require an engineer's time is findable in seconds.

Can agents brief reps before calls?

Yes. Agents assemble pre-call briefs from account history, competitive intel, and product knowledge.

Does the knowledge base get better as more questions are answered?

Yes. Every time an engineer answers a technical question in Slack, that answer becomes part of the searchable knowledge base. The rate of interruptions drops over time as the knowledge accumulates.

Can agents draft follow-up emails from call transcripts?

Yes. An agent reads the call transcript, drafts the follow-up in the rep's voice, and leaves it ready for review. The commitments from the call are included.

Do battlecards and competitive intel stay current?

Yes. Self-writing docs assemble competitive intel from your team's actual conversations about competitors, not from a static document someone wrote last year. The intel reflects what your team is hearing this quarter.

Can the AI synthesise across multiple calls about the same prospect?

Yes. The AI assistant draws from every call transcript, email, and Slack thread about an account and produces a cited synthesis.

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.