1 category · Named, not rankedRelevance AI
Standing by category
| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| AI marketing agents | Marketing | 0% | 43 of 157 | 17% | 6 | under 10 labels · led by HubSpot Breeze at 24% |
Movement
By model
How each model treated Relevance AI across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 1 | 0 | 0 | 1 |
| Perplexity Sonar | 0 | 1 | 0 | 0 | 1 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 2 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 1 | 0 | 0 | 1 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 1 | 1 |
By framing
What the models said for it
Verbatim evidence the judge attached to positive labels.
“Relevance AI and similar platforms are best when teams want to build tailored agents” Perplexity Sonar · AI marketing agents · comparative prompt · alternative
“Focuses on data transparency and audit trails.” Gemini 3.5 Flash · AI marketing agents · comparative prompt · alternative
“Best for: Custom AI agent building” Kimi K2 · AI marketing agents · comparative prompt · alternative
And against it
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“frameworks for building custom agent systems that require developer resources” Muse Glimmer 30B · AI marketing agents · comparative prompt · soft negative
Named alongside
The products named in the same answers as Relevance AI, over the 15 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Relevance AI was named but was not.ShowHide
Named alongside
What carried it into the answer
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 15 of the 15 answers that named Relevance AI and are not a share of its labels.
Domains cited
Forty-five of the forty-five domain citations in answers naming Relevance AI came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
What it publishes
ShowHide
What it publishes
ShowHide| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Template or tool | 643 | undated | CRM, SEO | ||
| Blog | 236 | 0 | 2026-02-26 | SEO, CRM | |
| Comparison | 42 | 0 | 2026-05-21 | ||
| Report or ebook | 39 | 0 | 2023-04-20 | CRM, Enrichment | |
| Glossary or explainer | 15 | 0 | 2025-07-18 | ||
| Case study | 12 | 0 | 2024-04-23 | ||
| Webinar or virtual event | 11 | 0 | 2026-03-01 | ||
| Conference or event | 11 | undated | |||
| News or press | 6 | undated |
Most recent
- 2026-05-21Arcads alternatives comparison
- 2026-05-18Huggingface alternatives comparison
- 2026-03-01Webinar event agents webinar or virtual event
- 2026-02-26Adaptive context management for production ai agents blog
- 2026-02-16Replicate alternatives comparison
- 2026-02-12How we used ai to clean up feature flags and open sourced it blog
How it is countedHide how it is counted
Every page relevanceai.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
Follow Relevance AI
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
The company
Relevance AI is its own company.ShowHide
The company
In its own words
Stated by the vendor, not checked- Positioning
- Specialist AI Agents for Every Task
- For
- enterprise teams
- Price stated
- Free plan relevanceai.com/features/embed
- Free plan or trial
- Try for free relevanceai.com/features/embed
- Integrations claimed
- 1000 relevanceai.com · 2000 relevanceai.com/pricing pages disagree
- Certifications
- SOC 2GDPRSOC 2 Type II compliantSOC 2 Type II
- Customers named
- AutodeskCanvaQualifiedSend PaymentsZemblLightspeed CommerceRakuten AdvertisingLightspeed
- Not stated on the pages read
- Starting price, hosting
What Relevance AI's own pages state, read October 5, 2026: relevanceai.com, relevanceai.com/pricing, trust.relevanceai.com, relevanceai.com/features/embed, relevanceai.com/customers. A claimed page can correct any of them.
Claim this page
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Relevance AI's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Relevance AI, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for Relevance AI by email, built from the raw record of the edition. It shows:
- where Relevance AI is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name Relevance AI, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.