| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Workforce scheduling | Core HR and payroll | 2% | 12 of 108 | 0% | 1 | under 10 labels · led by Deputy at 37% | newNew since September 2026: not ranked then, 2% now. |
| Workforce management suites | Core HR and payroll | 0% | 43 of 78 | 33% | 3 | under 10 labels · led by Rippling at 17% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Workforce scheduling | 0% | 2% | newNew since September 2026: not ranked then, 2% now. | New this edition | Rank 12 of 108, unchanged |
| Workforce management sui | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 22 → 43 of 78 |
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 13 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 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 1 | 0 | 0 | 1 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 1 | 0 | 0 | 0 | 1 |
| 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 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 1 | 0 | 1 | 2 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |
Verbatim evidence the judge attached to positive labels.
“Legion, UKG Dimensions, Dayforce, and Deputy are the top recommendations” Mistral Small · Workforce scheduling · direct prompt · first choice
“unless your workforce is mostly hourly/frontline, in which case Legion may be a better fit” GPT-5.4 mini · Workforce management sui · direct prompt · alternative
“Worth including when optimized scheduling is the main problem” GPT-6 Luna · Workforce management sui · comparative 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.
“make implementation a major part of your reference checks... a customer report of disorganized project management and delays” GPT-6 Luna · Workforce management sui · 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 15 of the 15 answers that named Legion WFM and are not a share of its labels.
Thirty-eight of the forty-five domain citations in answers naming Legion WFM came from somebody else's page.
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.
What Legion WFM's own pages state, read October 5, 2026: pages.legion.co/legacy-wfm.html, pages.legion.co/intelligent-wfm.html, legion.co/forrester-tei-study-legion-wfm, legion.co/wfm-software-generative-ai-whitepaper, legion.co/product-tour-ai-in-legion-wfm-on-demand. A claimed page can correct any of them.
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 Legion WFM'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 Legion WFM, 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 Legion WFM by email, built from the raw record of the edition. It shows: