Fabric for startups

Startups produce context faster than they can retain it. A product decision is made on a call and never written down. A competitive insight surfaces in a Slack thread and sinks. An investor asks a question the team answered three months ago, but nobody can find the answer. A new hire joins and spends their first two weeks piecing together what's happening from fragments across Notion, Google Docs, Slack, and the memories of people too busy to explain it properly. Speed is the whole point of being a startup, but speed without a system for retaining what you learn means you re-debate resolved questions, re-discover known information, and lose the context that should be compounding into an advantage.

Fabric gives early-stage teams one searchable workspace where every decision, meeting, research insight, and document is findable, by anyone, at any time, with an AI that remembers what was decided and why.

Every decision, findable forever

The most expensive thing a startup loses isn't a file. It's the answer to "why did we decide that." Product direction, pricing strategy, hiring decisions, architecture choices, go-to-market pivots. Each was discussed, debated, and resolved. Most were never documented. The ones that were are in a Google Doc, a Slack thread, or a meeting that nobody recorded.

Fabric captures decisions as a byproduct of the work. Record meetings with AI voice notes and the transcript is searchable. Write decisions in notes and docs and they're findable by meaning. Forward important emails to email-to-note and they join the record. When someone asks "why did we switch our pricing model," AI search finds the meeting where it was discussed, the note where the rationale was captured, and the research that informed the decision.

The AI assistant goes further. Ask it to summarise the thinking behind a past decision, pull together everything the team has discussed about a topic, or prepare context for a board meeting by synthesising across months of notes, research, and meeting records.

Competitive and market intelligence that compounds

Every startup does competitive research. Few retain it. You screenshot a competitor's pricing page, save an article about their raise, take notes after a prospect mentions them. Within a month, the intelligence is scattered across personal drives, browser bookmarks, and Slack channels you'd have to scroll through for twenty minutes.

Fabric's AI search reads inside every file type, including text in screenshots and images. Ask "what's [competitor]'s enterprise pricing" and find the screenshot, the call notes, and the article together. The AI assistant synthesises across your competitive library: compare two competitors, summarise a competitor's recent moves, or identify gaps in your intelligence.

Over time, the competitive library becomes an institutional asset. New team members search it and get up to speed. Returning to a competitor you tracked six months ago means the history is already there. The research compounds rather than resetting every quarter.

Onboarding that doesn't depend on one person's availability

Early-stage startups add people fast, and every new hire needs context that lives in the heads of the founders. The product vision, the technical architecture, the customer segments, the sales playbook, the reasons behind a dozen decisions. Without a system, onboarding means monopolising a founder's time for a week, and the new hire still only gets whatever that founder remembers to cover.

A shared Fabric workspace gives new hires one place to search. They ask the AI about the product architecture and get an answer drawn from design docs and meeting transcripts. They search for the sales playbook and find it alongside the competitive research and customer call notes. The context exists in the system, searchable and complete, rather than locked in a founder's calendar.

For the full onboarding workflow, see onboarding new team members. For the standing knowledge base that new hires draw from, see team wiki.

Investor materials and data rooms

Fundraising generates its own body of documents: pitch decks, financial models, cap tables, product demos, customer references, competitive analyses. Sharing them securely with individual investors and tracking who's actually reviewing the material is the difference between an informed follow-up and a cold "just checking in."

Publish your investor materials with password protection and link analytics. Create individually named tracking links per investor and see who's engaged with the deck, who's opened the financial model, and who hasn't looked at anything. Update a document and the link serves the current version. For full due diligence sharing, see the data room workflow.

Use cases for startups

The workflows startups run in Fabric: capturing meeting notes from every call and standup, maintaining project documentation that survives team changes, building a team wiki for processes and know-how, onboarding new team members without monopolising founder time, tracking competitive research and market research that compounds, sharing investor materials via data rooms and sales collateral, running a lightweight CRM from deal spaces, brainstorming on the canvas, content planning for marketing, and hosting a press kit behind one always-current link.

A startup's day in Fabric

Morning standup. The team runs a quick standup. Someone records it with voice notes. The transcript joins the workspace alongside yesterday's and last week's. Decisions and blockers are searchable, not lost in a video call that nobody will re-watch.

Mid-morning. The founder prepares for an investor meeting. She asks the AI assistant to pull together the latest metrics, the competitive landscape summary, and the product roadmap notes. The AI synthesises from across the workspace and she has a brief in minutes.

Lunch. A new engineer on his second day searches the workspace for "authentication architecture." He finds the design doc, the meeting where the approach was debated, and the follow-up note explaining why OAuth was chosen over SAML. He's productive by Wednesday instead of the following Monday.

Afternoon. The head of sales saves a competitor's updated pricing page to the workspace. AI search reads the text in the screenshot. Next quarter, when a prospect asks how the pricing compares, the answer is one search away.

End of day. The founder shares the updated pitch deck with three investors via individually tracked links. By tomorrow morning, she'll know who opened it.

Get started

Give your startup a shared brain where every decision, every insight, and every document is searchable by anyone on the team. Try Fabric free.

See pricing for teams. For individual founders managing their own context, see Fabric for founders. For solo builders, see Fabric for indie hackers.

FAQs

Can the AI recall past decisions and the reasoning behind them?

Yes. The AI assistant works from everything in the workspace: meeting transcripts, notes, documents, and emails. Ask it why a decision was made and it finds the relevant meeting, the note, and the research that informed it.

Can we record and transcribe standups and meetings?

Yes. AI voice notes capture and transcribe any meeting. The transcript becomes a searchable part of the workspace. No meeting bot required.

Can new hires get up to speed without a founder walking them through everything?

Yes. New team members search the workspace and ask the AI for context. The full history of decisions, architecture choices, and product thinking is searchable. See onboarding new team members for the full workflow.

Can we track competitive intelligence over time?

Yes. Save screenshots, articles, call notes, and any other competitive material to the workspace. AI search reads text inside images and searches by meaning. The library grows into a timeline of each competitor's evolution. See competitive research.

Can we share our pitch deck with investors and track who views it?

Yes. Publish with password protection and link analytics. Create named tracking links per investor. See when they open the deck, how long they spend, and which documents they view.

Can we set up a data room for fundraising?

Yes. Share a collection of documents with password-protected, tracked links. See the full data room workflow for due diligence sharing.

Can we use Fabric as a lightweight CRM?

Yes. Create a space per prospect with call notes, proposals, and follow-up tasks. Search across all deals by meaning. See the CRM use case for the full pattern.

Can we build a team wiki for processes and know-how?

Yes. Use a shared space as a team wiki for processes, playbooks, and institutional knowledge. The AI answers questions from the wiki directly.

Can we use the AI to prepare for board meetings?

Yes. Ask the assistant to synthesise across the workspace: recent metrics, product progress, competitive landscape, and open questions. It pulls context from months of notes, documents, and meeting records.

Can we collaborate in real time?

Yes. Real-time collaboration supports live cursors, threaded comments, @mentions, and follow mode across notes, canvas, kanban, and annotations.

Can we use Fabric alongside Notion, Slack, and our other tools?

Yes. Fabric connects to Google Drive, Dropbox, Notion, and Gmail. It works alongside your existing stack rather than replacing it.

Is our data secure?

Yes. Fabric uses AES-256 encryption, is CASA Tier 2 compliant, and does not use your data to train AI models. Investor materials, product docs, and competitive intel are private by default.

How is this different from using Notion as our startup wiki?

Notion is a page-based tool that requires deliberate structure and maintenance. Fabric holds every type of content (documents, meeting transcripts, emails, screenshots, voice recordings, PDFs) and makes all of it searchable by meaning, with an AI that synthesises across the full history. The difference matters at speed: when things move fast, the knowledge is captured by saving it, not by filing it into a wiki structure.