| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Contingent workforce management | Workforce planning and analytics | 2% | 18 of 121 | 57% | 44 | criticized challenger | =heldSince September 2026: 2% → 2%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Staffing agency platforms | Talent acquisition | 0% | 91 of 136 | 50% | 2 | under 10 labels · led by Zoho Recruit at 22% |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Contingent workforce man | 2% | 2% | =heldSince September 2026: 2% → 2%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 18 of 121, unchanged |
| Staffing agency tools | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 91 of 136, 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 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 | 1 | 1 | 2 |
| GPT-5.4 mini | 0 | 1 | 1 | 1 | 3 |
| Gemini 3.5 Flash | 0 | 1 | 0 | 5 | 6 |
| Perplexity Sonar | 0 | 0 | 2 | 0 | 2 |
| Grok 4.1 Fast | 1 | 0 | 0 | 4 | 5 |
| Mistral Small | 1 | 0 | 3 | 2 | 6 |
| DeepSeek V4 Flash | 1 | 0 | 0 | 2 | 3 |
| Llama 4 Maverick | 0 | 0 | 2 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 3 | 3 |
| Kimi K2 | 1 | 0 | 1 | 2 | 4 |
| GLM 4.7 FlashX | 0 | 1 | 0 | 2 | 3 |
| MiniMax M2.5 | 1 | 0 | 0 | 0 | 1 |
| GPT-6 Luna | 1 | 0 | 0 | 1 | 2 |
| Muse Glimmer 30B | 1 | 0 | 0 | 3 | 4 |
Verbatim evidence the judge attached to positive labels.
“Specifically designed for contingent workforce management... making it ideal for global mid-market companies needing a robust, scalable solution” Mistral Small · Contingent workforce man · direct prompt · first choice
“Leading enterprise VMS for large-scale, global programs... SAP Fieldglass and Beeline often top lists for market share and features.” Grok 4.1 Fast · Contingent workforce man · comparative prompt · first choice
“For large enterprises with complex contingent workforce programs, SAP Fieldglass and Magnit are the leading choices.” MiniMax M2.5 · Contingent workforce man · comparative prompt · first choice
“For large enterprises with mature contingent programs, SAP Fieldglass or Beeline remain the market leaders” DeepSeek V4 Flash · Contingent workforce man · comparative prompt · first choice
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.
“traditional enterprise solutions (like SAP Fieldglass, Beeline, or Workday VNDLY) are usually not viable options” Gemini 3.5 Flash · Contingent workforce man · budget prompt · hard negative
“Enterprise Options to Avoid (Too Expensive) ... SAP Fieldglass | $50,000-$500,000+ | Enterprise-only pricing” Kimi K2 · Contingent workforce man · budget prompt · hard negative
“Over-Engineered Legacy VMS Platforms (e.g., SAP Fieldglass, Beeline)... Excessive Complexity and Costs” Gemini 3.5 Flash · Contingent workforce man · negative prompt · hard negative
“Avoid enterprise-heavy solutions like SAP Fieldglass or standard Beeline Enterprise” Kimi K2 · Contingent workforce man · direct prompt · hard negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 149 of the 155 answers that named SAP Fieldglass and are not a share of its labels.
474 of the 474 domain citations in answers naming SAP Fieldglass 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 SAP Fieldglass's own pages state, read September 28, 2026: sap.com/research/why-sap-fieldglass-is-transforming-workforce-management, sap.com/products/spend-management/about-fieldglass.html, sap.com/products/hcm/fieldglass-worker-profile-management.html, sap.com/products/technology-platform/fieldglass-solutions-joule.html, sap.com/products/spend-management/fieldglass-sandbox-environment.html. 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 SAP Fieldglass'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 SAP Fieldglass, 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 SAP Fieldglass by email, built from the raw record of the edition. It shows: