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Process mining · October 2026 Edition

Apromore vs Microsoft Power Automate Process Mining

Two of fourteen models named Apromore first on the direct prompt; four named Microsoft Power Automate Process Mining. Apromore was named by thirteen of the fourteen models and Microsoft Power Automate Process Mining by eleven and Apromore carries 37 labels and Microsoft Power Automate Process Mining 21, so the shares are not directly comparable.

Apromore

accepted challenger

Named in one category this edition.

Named in one category this edition.

First-choice share19%14%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate3%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#2A position in a field of 9; printed, not drawn.
Labels3721A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Apromore reading right to left. Rank and label count are printed, not drawn.UiPath Process Mining was named alongside these two in nine of the fourteen direct answers. Apromore vs IBM Process Mining · Apromore vs UiPath Process Mining · Apromore vs Microsoft Power Automate

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen 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 process mining page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
ApromoreFirst choices, of fourteen modelsMicrosoft Power Automate Process Mining
Direct24
Paraphrase01
Comparative00
Budget-constrained821 against Microsoft Power Automate Process Mining
Scale-constrained11
Negative001 against Apromore · 2 against Microsoft Power Automate Process Mining
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, Apromore and Microsoft Power Automate Process Mining were named in the same answer thirty-four times, of the 95 answers naming Apromore and the 62 naming Microsoft Power Automate Process Mining. In those answers Microsoft Power Automate Process Mining took the first choice ten times and Apromore seven.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Apromore and Microsoft Power Automate Process Mining stood in it.
ModelDirectMPParaphraseMPComparativeMPBudget-constrainedMPScale-constrainedMPNegativeMP
Claude Haiku 4.5MP
GPT-5.4 mini
Gemini 3.5 FlashMPMPMPMPMP
Perplexity SonarMPMPMP
Grok 4.1 FastMP
Mistral SmallMP
DeepSeek V4 FlashMPMP
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2MPMP
GLM 4.7 FlashXMP
MiniMax M2.5MP
GPT-6 LunaMPMPMP
Muse Glimmer 30BMP
ApromoreMP Microsoft Power Automate Process Mining first choice named as an alternative argued againstblank: not namedEach cell is one answer, Apromore on the left and Microsoft Power Automate Process Mining on the right.

The direct prompt

The plain question, one answer per model, grouped by where Apromore and Microsoft Power Automate Process Mining stood in it.

Apromore first, Microsoft Power Automate Process Mining an alternative

2 of 14 modelsMicrosoft Power Automate Process Mining was named in the answer but not as the choice, or not at all.
MiniMax M2.5Apromore, Celonis Process Intelligence Platform alternatives: IBM Process Mining, Microsoft Power Automate Process Mining, UiPath Process Mining
GPT-6 LunaApromore alternatives: Power Automate Process Mining, SAP Signavio Process Intelligence, UiPath Process Mining

Microsoft Power Automate Process Mining first, Apromore an alternative

4 of 14 modelsApromore was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashMicrosoft Power Automate Process Mining alternatives: Apromore, KYP.ai, UiPath Process Mining
Perplexity SonarMicrosoft Power Automate Process Mining alternatives: SAP Signavio Process Intelligence, UiPath Process Mining
DeepSeek V4 FlashMicrosoft Power Automate Process Mining, UiPath Process Mining alternatives: Mindzie, Minit, ProcessMind
Kimi K2Microsoft Power Automate Process Mining, Mindzie alternatives: Apromore, MEHRWERK, QPR ProcessAnalyzer

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Microsoft Power Automate alternatives: Apromore, ProcessMind, QPR ProcessAnalyzer
Grok 4.1 FastMicrosoft Power Automate alternatives: Apromore, UiPath Process Mining
GLM 4.7 FlashXMindzie alternatives: ABBYY Timeline, Apromore, Microsoft Power Automate
Muse Glimmer 30BDecisions, ProcessMaker alternatives: Microsoft Power Automate Process Mining, Noxus

Neither was named

4 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniUiPath Process Mining alternatives: Celonis Process Intelligence Platform, SAP Signavio Process Intelligence
Mistral SmallCelonis Process Intelligence Platform alternatives: SAP Signavio Process Intelligence, UiPath Process Mining
Llama 4 MaverickProcessMaker
Qwen 3.7 FlashEverflow Process Intelligence, ProcessMaker alternatives: SAP Signavio Process Intelligence, UiPath Process Mining

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
Apromore leads by four points.
Apromore12%#3 of 12
Microsoft Power Automate Process Mining8%#4 of 12
The full small business standing →
Mid-marketThe figures above
Apromore leads by five points.
Apromore19%#1 of 9
Microsoft Power Automate Process Mining14%#2 of 9
The full mid-market standing →
Enterprise
The order flips: Microsoft Power Automate Process Mining leads at enterprise.
Microsoft Power Automate Process Mining20%#2 of 8
Apromore0%#7 of 8
The full enterprise standing →

What the models said about Apromore

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

“Limited compared to commercial version; requires technical expertise” Kimi K2 · negative prompt · soft negative
“Mid-Market & Agile Specialized Tools (e.g., Apromore, Fluxicon Disco, IBM Process Mining): Often much faster to implement, cost-effective” Gemini 3.5 Flash · scale prompt · first choice
“I'd recommend starting with Apromore's free Community Edition if you have some technical capability” DeepSeek V4 Flash · budget prompt · first choice
“For most budget-conscious companies, I'd recommend starting with Apromore Community Edition” Kimi K2 · budget prompt · first choice

What the models said about Microsoft Power Automate Process Mining

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

“Avoid or be cautious with Microsoft Power Automate Process Mining if you expect high volumes” Mistral Small · negative prompt · hard negative
“I wouldn’t start with Microsoft Power Automate Process Mining if the budget is especially tight” GPT-6 Luna · budget prompt · soft negative
“it can carry heavy add-on licensing costs (such as a $5,000/month tenant capacity add-on)” Gemini 3.5 Flash · negative prompt · soft negative
“Best for Microsoft-Centric Companies: Microsoft Power Automate Process Mining ... this is the most seamless and cost-effective commercial option.” Gemini 3.5 Flash · budget prompt · first choice
“Best Overall & Best for Microsoft Ecosystems: Microsoft Power Automate Process Mining (formerly Minit)” Gemini 3.5 Flash · direct prompt · first choice
“UiPath Process Mining or Microsoft Power Automate Process Mining are the safest bets” DeepSeek V4 Flash · direct 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.