| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Cash flow forecasting | Treasury and cash | 0% | 100 of 101 | 60% | 5 | under 10 labels · led by Agicap at 13% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. |
| Financial close management | Accounting and close | 0% | 73 of 85 | 100% | 1 | under 10 labels · led by FloQast at 55% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. |
| FP&A platforms | Planning and analysis | 0% | 64 of 74 | 100% | 1 | under 10 labels · led by Planful at 20% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. |
| Treasury management systems | Treasury and cash | 0% | 92 of 124 | 0% | 1 | under 10 labels · led by Trovata at 28% | newNew since September 2026: not ranked then, 0% now. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Cash flow forecasting | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 81 → 100 of 101 |
| Financial close manageme | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 65 → 73 of 85 |
| FP&A platforms | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 21 → 64 of 74 |
| Treasury management syst | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 92 of 124, 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 10 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 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 0 | 1 | 1 |
| 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 | 1 | 1 |
| Kimi K2 | 0 | 1 | 0 | 2 | 3 |
| GLM 4.7 FlashX | 0 | 0 | 1 | 1 | 2 |
| MiniMax M2.5 | 0 | 0 | 1 | 0 | 1 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |
Verbatim evidence the judge attached to positive labels.
“Best for: Very small businesses just starting out ... Cons: Manual data entry, no automatic syncing with bank accounts” Kimi K2 · Cash flow forecasting · budget 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.
“## 1. Excel/Google Sheets (Untethered) Why to avoid: - Manual data entry errors” GLM 4.7 FlashX · Cash flow forecasting · negative prompt · hard negative
“AI analyses flag Excel workflows as a top "avoid" for scaling.” Grok 4.1 Fast · Cash flow forecasting · negative prompt · hard negative
“relying solely on spreadsheets is the riskiest approach” Kimi K2 · Cash flow forecasting · negative prompt · hard negative
“Cons: High risk of human error ("fat finger" mistakes), version control issues, and lack of an automated audit trail.” Qwen 3.7 Flash · Financial close manageme · budget 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 37 of the 38 answers that named Excel/Google Sheets and are not a share of its labels.
No domain is on file for Excel/Google Sheets, 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 Excel/Google Sheets'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 Excel/Google Sheets, 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 Excel/Google Sheets by email, built from the raw record of the edition. It shows: