Finance AI Index
Index Planning and analysis FP&A platforms › Fathom vs Datarails
FP&A platforms · September 2026 Edition

Fathom vs Datarails

Zero of twelve models named Fathom first on the direct prompt; one named Datarails. Fathom was named by ten of the twelve models and Datarails by twelve and Fathom carries 10 labels and Datarails 45, so the shares are not directly comparable.

Fathom

accepted challenger

Named in nine categories this edition.

Datarails

accepted challenger

Named in ten categories this edition.

First-choice share10%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#8A position in a field of 16; printed, not drawn.
Labels1045A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Fathom reading right to left. Rank and label count are printed, not drawn.Pigment was named alongside these two in eight of the twelve direct answers. Vena vs Fathom · Vena vs Datarails · Pigment vs Fathom

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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 FP&A platforms page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
FathomFirst choices, of twelve modelsDatarails
Direct01
Paraphrase01
Comparative01
Budget-constrained501 against Datarails
Scale-constrained00
Negative003 against Datarails
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Across every category in the September 2026 Edition, Fathom and Datarails were named in the same answer fifty-four times, of the 224 answers naming Fathom and the 273 naming Datarails. In those answers Datarails took the first choice six times and Fathom fifteen.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Fathom and Datarails stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Fathom Datarails first choice named as an alternative argued againstblank: not namedEach cell is one answer, Fathom on the left and Datarails on the right.

The direct prompt

The plain question, one answer per model, grouped by where Fathom and Datarails stood in it.

Datarails first, Fathom not the choice

1 of 12 modelsFathom was named in the answer but not as the choice, or not at all.
DeepSeek V4 FlashDatarails alternatives: Planful, Prophix, Vena

Neither was the first choice, one was named

6 of 12 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniPlanful, Vena alternatives: Cube, Datarails
Grok 4.1 FastCube, Vena alternatives: Datarails, Pigment
Mistral SmallCentage alternatives: Abacum, Aleph, Datarails, Workday Adaptive Planning
Qwen 3.7 FlashPigment alternatives: Aleph, Centage, Datarails, Workday Adaptive Planning
GLM 4.7 FlashXPigment alternatives: Aleph, Centage, Cube, Datarails, Planful, Prophix, Vena, Workday Adaptive Planning
MiniMax M2.5Pigment alternatives: Aleph, Centage, Datarails, Workday Adaptive Planning

Neither was named

5 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Planful alternatives: Pigment, Prophix, Vena
Gemini 3.5 FlashDrivetrain alternatives: Bob Finance, Cube, Planful
Perplexity SonarPlanful alternatives: Aleph, Centage, Pigment, Prophix, Vena
Llama 4 MaverickPigment alternatives: Aleph, Centage, Workday Adaptive Planning
Kimi K2Pigment alternatives: Aleph, Centage, Workday Adaptive Planning

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
Fathom leads by eleven points.
Fathom13%#2 of 13
Datarails2%#5 of 13
The full small business standing →
Mid-marketThe figures above
Fathom leads by six points.
Fathom10%#5 of 16
Datarails4%#8 of 16
The full mid-market standing →
Enterprise
Fathom is not named for this buyer.
Fathomnot named
Datarails0%#– of 12
The full enterprise standing →

What the models said about Fathom

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“Fathom (cheapest) or Clockwork (best overall for forecasting + AI) are your strongest picks” DeepSeek V4 Flash · budget prompt · first choice
“Fathom – Best Value for Money ... Fathom is the most cost-effective professional solution” Kimi K2 · budget prompt · first choice

What the models said about Datarails

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.

“The Pitfall (specifically Datarails): ... its pricing has risen significantly... the ROI may not add up.” Gemini 3.5 Flash · negative prompt · hard negative
“Avoid pricier ones like Jirav (~$10K/year), Cube/Datarails ($1K+/month)” Grok 4.1 Fast · budget prompt · hard negative
“Datarails is often the strongest all-around pick — Excel-based, strong consolidation and variance analysis, faster to ROI” DeepSeek V4 Flash · direct prompt · first choice
“Start with Datarails or Vena if your team is comfortable in Excel and wants minimal disruption” Kimi K2 · 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.