AI IT support agents · October 2026 Edition
Freshservice vs Intercom Fin
Three of fourteen models named Freshservice first on the direct prompt; one named Intercom Fin. Freshservice was named by thirteen of the fourteen models and Intercom Fin by eleven and Freshservice carries 17 labels and Intercom Fin 21, so the shares are not directly comparable.
Named in nine categories this edition.
Named in two categories this edition.
First-choice share9%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#3A position in a field of 8; printed, not drawn.
Labels1721A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Freshservice reading right to left. Rank and label count are printed, not drawn.Freshservice vs Zendesk AI Agents · Freshservice vs Freshdesk · Freshservice vs Zoho Desk
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the AI IT support agents page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
FreshserviceFirst choices, of fourteen modelsIntercom Fin
Direct31
Paraphrase21
Comparative001 against Intercom Fin
Budget-constrained01
Scale-constrained00
Negative002 against Intercom Fin
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Freshservice and Intercom Fin stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | |||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | | | ||||
| Perplexity Sonar | | | | |||
| Grok 4.1 Fast | | | ||||
| Mistral Small | | |||||
| DeepSeek V4 Flash | | |||||
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | | | | |||
| Kimi K2 | | | | | ||
| GLM 4.7 FlashX | | | ||||
| MiniMax M2.5 | | | ||||
| GPT-6 Luna | | |||||
| Muse Glimmer 30B |
Freshservice Intercom Fin first choice named as an alternative argued againstblank: not namedEach cell is one answer, Freshservice on the left and Intercom Fin on the right.The direct prompt
The plain question, one answer per model, grouped by where Freshservice and Intercom Fin stood in it.
Both were the first choice
1 of 14 modelsThe answer named them together, and the judge labeled each a first choice.Qwen 3.7 FlashFreshservice, Intercom Fin alternatives: Jira Service Management, Zendesk AI Agents
Freshservice first, Intercom Fin not the choice
2 of 14 modelsIntercom Fin was named in the answer but not as the choice, or not at all.Mistral SmallAtera, Freshservice, SysAid alternatives: Conversica, Forethought, Genesys Cloud CX
Llama 4 MaverickFreshservice, SysAid alternatives: DeskFerry, HelpDesk, Relevance AI, n8n
Neither was the first choice, one was named
3 of 14 modelsThe answer put something else first and named one of the two as an alternative.Claude Haiku 4.5Risotto alternatives: Freshservice, Moveworks, Zoho Desk, eesel AI
Perplexity SonarFreshservice with Freddy AI alternatives: Ada, Intercom Fin, Kustomer
MiniMax M2.5Decagon alternatives: Forethought, Freshservice, Jira Service Management, SysAid, eesel AI
Neither was named
8 of 14 modelsThe answer made no first choice from these two in this category.GPT-5.4 miniFreshservice with Freddy AI alternatives: Moveworks, ServiceNow Now Assist, SysAid
Gemini 3.5 FlashRisotto alternatives: Atomicwork, Decagon, Siit
Grok 4.1 FastFreshservice with Freddy AI alternatives: Aisera, Freshdesk, Moveworks, Zendesk AI Agents
DeepSeek V4 FlashFreshservice with Freddy AI alternatives: SysAid, eesel AI
Kimi K2Rezolve.ai alternatives: Aisera, Moveworks
GLM 4.7 FlashXForethought alternatives: Fini, Moveworks, ServiceNow Now Assist
GPT-6 LunaFreshservice with Freddy AI Agent alternatives: Jira Service Management, Moveworks
Muse Glimmer 30BAtomicwork Atom, Freshworks Freshservice with Freddy AI
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Intercom Fin leads by six points.
Intercom Fin8%#2 of 9Freshservice2%#7 of 9Mid-marketThe figures above
The order flips: Freshservice leads at mid-market.
Freshservice9%#1 of 8Intercom Fin6%#3 of 8Enterprise
The order flips: Intercom Fin leads at enterprise.
Intercom Fin2%#– of 6Freshservice0%#6 of 6What the models said about Freshservice
No label in this category carried a quote.
What the models said about Intercom Fin
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“may lack the deep "action-oriented" integrations (like modifying Active Directory) that true IT support agents require” Qwen 3.7 Flash · comparative prompt · soft negative
“⚠️ Heavy ecosystem lock-in — limited flexibility for external CRMs ... Pricing scales steeply with conversation volume” Kimi K2 · negative prompt · soft negative
“failures plague many (e.g., Zendesk AI, Intercom Fin, early Moveworks/Aisera setups per reviews)” Grok 4.1 Fast · negative prompt · soft negative
“If I had to pick one budget-first option for IT support, I'd choose Intercom Fin” Perplexity Sonar · budget prompt · first choice
“Top Choice: Intercom (Fin AI Agent) ... gold standard for B2B "conversational" AI” Qwen 3.7 Flash · direct prompt · first choice
“Top Recommendation: Intercom Fin” MiniMax M2.5 · paraphrase prompt · first choice
Also compared
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.