DABYTE DATA DESK · SaaS & AI TOOLS

AI Visibility Index: which SaaS and AI-tool brands do answer engines actually name?

Answer. Across a fixed panel of 12 category buyer prompts on 2 AI engines, Notion leads with 33.4% share of answer, followed by HubSpot (20.9%) and Salesforce (20.9%). The headline finding is the gap, not the ranking: 13 of 20 tracked brands combine high commercial intent with low visibility — they are largely absent from the answers their own buyers receive. Measured 2026-07-23 by DABYTE.

Last measured · next re-measurement monthly · method sonar · engines: openai, perplexity · methodology

By D. Popov, Editor, DABYTE Data Desk · published by VECTORY

The index — share of answer by brand

Each cell is the percentage of the 12-prompt panel in which that engine named the brand. Intent is the commercial-intent score of the category the brand competes in; the quadrant combines the two.

DABYTE AI Visibility Index — SaaS & AI tools, measured 2026-07-23. Share of answer = % of a fixed 12-prompt buyer panel in which the brand is named by the engine. Source: DABYTE, method sonar.
#Brand Visibilityopenaiperplexity IntentQuadrant
1Notion33.4%41.7%25.0%78Niche (visibility gap)
2HubSpot20.9%25.0%16.7%82Niche (visibility gap)
3Salesforce20.9%25.0%16.7%85Niche (visibility gap)
4Slack20.8%33.3%8.3%70Niche (visibility gap)
5Figma12.5%16.7%8.3%74Niche (visibility gap)
6Zapier12.5%16.7%8.3%72Niche (visibility gap)
7Airtable12.5%16.7%8.3%68Niche (visibility gap)
8Monday.com12.5%8.3%16.7%71Niche (visibility gap)
9GitHub Copilot12.5%16.7%8.3%76Niche (visibility gap)
10Miro12.5%16.7%8.3%67Niche (visibility gap)
11Asana8.3%8.3%8.3%69Niche (visibility gap)
12ClickUp8.3%8.3%8.3%66Niche (visibility gap)
13Linear8.3%8.3%8.3%63Low performance
14Jasper8.3%8.3%8.3%61Low performance
15Intercom8.3%16.7%0.0%70Niche (visibility gap)
16Amplitude8.3%8.3%8.3%60Low performance
17Webflow4.2%8.3%0.0%64Low performance
18Retool4.2%8.3%0.0%62Low performance
19Otter.ai4.2%8.3%0.0%52Low performance
20Copy.ai0.0%0.0%0.0%55Low performance

Reading the table: a brand at 25% was named in one answer out of four. Because engines name only a few sources per response, mid-table positions change faster than the leaders — which is why the DABYTE index is re-measured monthly rather than published once.

Quadrants — where the gaps are

Brands are placed by visibility (share of answer) against commercial intent. A “visibility gap” means buyers are actively asking and the brand is not in the answer.

Methodology

AI Visibility Index measures how often each brand is cited in AI-assistant answers across a fixed panel of 12 category prompts, on 2 engines (openai, perplexity). Visibility score = share of panel prompts where the brand is mentioned, averaged across engines (engine-weighted). Re-measured monthly. Paid placements never affect scores (editorial firewall).

Prompt panel (12 prompts, fixed between releases)

  1. best AI writing assistant for teams
  2. top project management software for startups
  3. best CRM for small business
  4. best AI coding assistant
  5. top no-code app builder
  6. best collaborative whiteboard tool
  7. best customer support helpdesk software
  8. top data analytics platform for product teams
  9. best workflow automation tool
  10. best AI note-taking app
  11. top design tool for product teams
  12. best knowledge base software

Rules

  • The panel is fixed between releases; changes are versioned in the changelog.
  • A brand counts as “named” when the engine's answer references the brand or its documented aliases.
  • Scores are engine-weighted, then rounded to one decimal.
  • Paid placement never affects a score. Commercial products of VECTORY (profiles, reports, measurement) live outside the scoring fields, and no brand in this table has paid to appear in it.
  • Where an engine could not be measured in a release, it is excluded and the weights are re-normalised — never filled with an assumed value.

Ownership disclosure

DABYTE is published by VECTORY, an AI-visibility company. That is disclosed here, in the page footer and in /humans.txt, because a measurement is only useful if you know who ran it. VECTORY sells measurement and advisory services; it does not sell positions in this index.

Machine access — free, no key

The dataset behind this page is published for both people and agents under CC BY 4.0. No sign-up, no API key, no rate limit gate.

How to cite

DABYTE AI Visibility Index — SaaS & AI Tools, 2026-07-23. dabyte.ai

Changelog

Questions

What does this index measure?

It measures share of answer: how often each SaaS/AI brand is named by AI assistants across a fixed panel of 12 category buyer prompts on 2 engines (openai, perplexity). A score of 40% means the brand was named in 40% of the panel's answers on that engine.

Which SaaS brand is most visible in AI answers?

In the 2026-07-23 measurement, Notion leads the DABYTE index with 33.4% share of answer, ahead of HubSpot (20.9%) and Salesforce (20.9%). Even the leader is absent from roughly two thirds of category answers.

Why are well-known brands invisible in AI answers?

Answer engines name only a handful of sources per response, and that selection is driven by retrievable, structured, current evidence rather than by brand size or ad budget. In this measurement 13 of 20 tracked brands sit in a visibility gap: high commercial intent, low share of answer.

How often is the index updated?

Monthly. Every re-measurement re-runs the full prompt panel on every engine and rebuilds this page from the resulting dataset, so the published numbers and the machine-readable files never drift apart. Each release is listed in the changelog below.

Can I reuse these numbers?

Yes — the dataset is published under CC BY 4.0. Cite as: “DABYTE AI Visibility Index — SaaS & AI Tools, 2026-07-23, dabyte.ai”. Machine-readable copies: /api/aiv.json, /aiv.csv, /index.md.