Who do AI assistants recommend for Design collaboration tools?
Generated 2026-07-08 · window 2026-06-10 → 2026-07-08 (28 days) · n = 84 sampled answers across 5 engines
Key findings
- 0% of the 104 businesses/products AI engines have ever recommended for this niche were not mentioned once in the last 28 days (0 of 104 known entities; window n = 84 answers). AI recommendations concentrate on a short list — everyone else is invisible.
- The #1 answer ("Figma") appears in 96.4% of sampled answers (81 of 84), recommended by 5 of 5 engines measured.
- 41.3% of everything AI recommends here is named by only ONE engine (43 of 104 recommended entities, n = 104) — the engines materially disagree.
- The most-cited source for this niche is vertexaisearch.cloud.google.com — cited in 14 of 84 sampled answers (16.7%).
Top 5 most-recommended
| # | Name | Share of answers | Answers | Avg. list position | Engine agreement |
|---|---|---|---|---|---|
| 1 | Figma (figma.com) | 96.4% | 81/84 | 3.6 | 5/5 |
| 2 | UXPin (uxpin.com) | 59.5% | 50/84 | 7.3 | 5/5 |
| 3 | Miro (miro.com) | 52.4% | 44/84 | 9.5 | 5/5 |
| 4 | Framer (framer.com) | 35.7% | 30/84 | 8.7 | 5/5 |
| 5 | Sketch | 31% | 26/84 | 6.7 | 5/5 |
Share = % of all 84 sampled answers in the window that recommend the entity. Engine agreement = engines recommending it at least once / engines measured.
Engine disagreement
Across the 5 engines measured (Claude (Anthropic), Gemini (Google), Grok (xAI), ChatGPT (OpenAI) and Perplexity), 104 distinct entities were recommended at least once. 43 of them (41.3%) were named by only a single engine (n = 104 entities). Ask a different AI, get a different answer.
What AI reads: most-cited sources
63 of 84 sampled answers cited at least one source.
| Source | Citations | Answers citing it | % of answers |
|---|---|---|---|
| vertexaisearch.cloud.google.com | 264 | 14/84 | 16.7% |
| uxpin.com | 42 | 33/84 | 39.3% |
| figma.com | 29 | 27/84 | 32.1% |
| uxpilot.ai | 25 | 24/84 | 28.6% |
| reddit.com | 22 | 21/84 | 25% |
| youtube.com | 16 | 14/84 | 16.7% |
| cpoclub.com | 15 | 10/84 | 11.9% |
| lucidlink.com | 9 | 9/84 | 10.7% |
| awesomic.com | 8 | 8/84 | 9.5% |
| eleken.co | 8 | 8/84 | 9.5% |
Chart data
Methodology
Sampled from the Orbator AI Recommendation Index: 84 answers collected 2026-06-10 → 2026-07-08 (28 days) across Claude (Anthropic) (n = 21), Gemini (Google) (n = 14), Grok (xAI) (n = 7), ChatGPT (OpenAI) (n = 21), Perplexity (n = 21) via their official APIs, with web search enabled where the engine supports it.
| Category sampled | n (answers) | Note |
|---|---|---|
| Design collaboration tools | 84 |
- Prompt design. Each category carries buyer-shaped prompts — the questions real buyers type ("best [category] for [audience]", "what should I use for [job]"). Prompts are strictly neutral: they never contain product or business names and never steer toward or away from anyone.
- Entity resolution. Every business/product named in an answer is extracted and resolved against a canonical registry, so name variants and domains count as one entity. Generic phrases are filtered and never become entities; suspected duplicates are human-reviewed.
- "Known" entities. The never-recommended stat counts every canonical entity the Index has ever extracted from this niche's answers (all time) and asks how many were not named even once inside the study window.
- Minimum sample. Categories with fewer than 20 sampled answers in the window are marked as small samples and should be treated as directional, not ranked — we publish stable numbers, not noise.
- Independence. Orbator sells AI-visibility tooling; measurement is identical for every business and product, customer or not. Rankings cannot be bought.
Full methodology: https://www.orbator.io/ai-index/methodology · Data © Orbator — free to cite with attribution to orbator.io.