| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| IT service management | IT operations and endpoint | 0% | 14 of 69 | 11% | 9 | under 10 labels · led by Freshservice at 58% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Incident management and on-call | IT operations and endpoint | 0% | 47 of 65 | 50% | 2 | under 10 labels · led by incident.io at 32% | newNew since September 2026: not ranked then, 0% now. |
| GRC platforms | Security operations | 0% | 60 of 75 | 100% | 1 | under 10 labels · led by Hyperproof at 19% |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| ITSM | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 8 → 14 of 69 |
| Incidents | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 47 of 65, unchanged |
| GRC | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 60 of 75, unchanged |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 1 | 0 | 1 | 2 |
| GPT-5.4 mini | 0 | 0 | 1 | 0 | 1 |
| Gemini 3.5 Flash | 0 | 2 | 0 | 0 | 2 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.20 | 0 | 1 | 1 | 0 | 2 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 1 | 0 | 0 | 1 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 1 | 1 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 1 | 0 | 1 |
| Muse Glimmer 30B | 0 | 0 | 1 | 1 | 2 |
Verbatim evidence the judge attached to positive labels.
“Known for being highly configurable, extremely cost-effective, and fully-featured without requiring a developer to maintain it.” Gemini 3.5 Flash · ITSM · scale prompt · alternative
“delivers enterprise-grade incident management capabilities at a price point suitable for mid-sized organizations” Claude Haiku 4.5 · Incidents · direct prompt · alternative
“The Best for Deep Customization & Value: HaloITSM” Gemini 3.5 Flash · ITSM · direct prompt · alternative
“UK/EU-based companies needing strong ITIL compliance” Kimi K2 · ITSM · paraphrase prompt · alternative
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.
““regulated organisations using ServiceNow, HaloITSM, and Freshservice. Ownership is unclear, evidence stays fragmented”” Muse Glimmer 30B · GRC · negative prompt · soft negative
“their smaller market presence and less mature ecosystems can mean fewer community resources and integration options” GLM 4.7 FlashX · ITSM · negative prompt · soft negative
“not ideal for businesses with advanced incident response needs, has limited scalability” Claude Haiku 4.5 · Incidents · negative prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 34 of the 34 answers that named HaloITSM and are not a share of its labels.
No domain is on file for HaloITSM, so its own site is not marked.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
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.
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 HaloITSM'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 HaloITSM, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for HaloITSM by email, built from the raw record of the edition. It shows: