Index › IT › IT operations and endpoint › Process mining › UiPath Process Mining vs ABBYY Timeline
Process mining · November 2026 Edition

UiPath Process Mining vs ABBYY Timeline

Three of fourteen models named UiPath Process Mining first on the direct prompt; one named ABBYY Timeline. UiPath Process Mining was named by fourteen of the fourteen models and ABBYY Timeline by nine and UiPath Process Mining carries 56 labels and ABBYY Timeline 16, so the shares are not directly comparable.

UiPath Process Mining

accepted challenger

Named in one category this edition.

ABBYY Timeline

accepted challenger

Named in one category this edition.

First-choice share10%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate18%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#8A position in a field of 11; printed, not drawn.
Labels5616A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, UiPath Process Mining reading right to left. Rank and label count are printed, not drawn.Apromore was named alongside these two in eleven of the fourteen direct answers. Microsoft Power Automate Process Mining vs UiPath Process Mining · Microsoft Power Automate Process Mining vs ABBYY Timeline · Apromore vs UiPath Process Mining

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.
UiPath Process MiningFirst choices, of fourteen modelsABBYY Timeline
Direct31
Paraphrase20
Comparative00
Budget-constrained002 against UiPath Process Mining
Scale-constrained00
Negative008 against UiPath Process Mining · 2 against ABBYY Timeline
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 November 2026 Edition, UiPath Process Mining and ABBYY Timeline were named in the same answer thirty-seven times, of the 164 answers naming UiPath Process Mining and the 44 naming ABBYY Timeline. In those answers ABBYY Timeline took the first choice zero times and UiPath Process Mining zero.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where UiPath Process Mining and ABBYY Timeline stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
UiPath Process Mining ABBYY Timeline first choice named as an alternative argued againstblank: not namedEach cell is one answer, UiPath Process Mining on the left and ABBYY Timeline on the right.

The direct prompt

The plain question, one answer per model, grouped by where UiPath Process Mining and ABBYY Timeline stood in it.

Both were the first choice

1 of 14 modelsThe answer named them together, and the judge labeled each a first choice.
Mistral SmallABBYY Timeline, Apromore, UiPath Process Mining alternatives: Microsoft Power Automate Process Mining

UiPath Process Mining first, ABBYY Timeline not the choice

2 of 14 modelsABBYY Timeline was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashMicrosoft Power Automate, UiPath Process Mining alternatives: Apromore, QPR ProcessAdvisor
GLM 4.7 FlashXUiPath Process Mining, process.science alternatives: IBM Process Mining, SAP Signavio Process Intelligence

Neither was the first choice, one was named

8 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Mindzie alternatives: Apromore, Microsoft Power Automate Process Mining, QPR ProcessAnalyzer, UiPath Process Mining
GPT-5.4 miniApromore alternatives: SAP Signavio Process Intelligence, UiPath Process Mining
Gemini 3.5 FlashMicrosoft Power Automate Process Mining alternatives: Apromore, UiPath Process Mining
Perplexity SonarApromore alternatives: Power Automate Process Mining, QPR ProcessAnalyzer, SAP Signavio Process Intelligence, UiPath Process Mining
Grok 4.20Microsoft Power Automate Process Mining alternatives: Apromore, UiPath Process Mining, process.science
DeepSeek V4 FlashProcessMind alternatives: Apromore, Microsoft Power Automate, QPR ProcessAnalyzer, UiPath Process Mining
Kimi K2Apromore, Microsoft Power Automate Process Mining alternatives: QPR ProcessAnalyzer, UiPath Process Mining
GPT-6 LunaApromore alternatives: Celonis Process Intelligence Platform, Power Automate Process Mining, SAP Signavio Process Intelligence, UiPath Process Mining

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Llama 4 MaverickMindzie
MiniMax M2.5Apromore, Microsoft Power Automate Process Mining alternatives: IBM Process Mining
Muse Glimmer 30BKye, Microsoft Power Automate Process Mining alternatives: Mindzie, Workfellow, process.science

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
UiPath Process Mining leads by four points.
UiPath Process Mining4%#7 of 13
ABBYY Timeline0%#– of 13
The full small business standing →
Mid-marketThe figures above
UiPath Process Mining leads by eight points.
UiPath Process Mining10%#3 of 11
ABBYY Timeline2%#8 of 11
The full mid-market standing →
Enterprise
UiPath Process Mining leads by two points.
UiPath Process Mining2%#6 of 10
ABBYY Timeline0%#9 of 10
The full enterprise standing →

What the models said about UiPath Process Mining

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

“mid-to-high cost and overkill for limited budgets” Grok 4.20 · budget prompt · hard negative
“shallower analytics depth than pure process mining leaders; challenges with large datasets, data integration ... Pricing and complexity can overwhelm.” Grok 4.20 · negative prompt · soft negative
“UiPath can connect mining to RPA, but rule-based automation may become brittle when processes change frequently” Perplexity Sonar · negative prompt · soft negative
“Microsoft Power Automate (Process Mining) and UiPath generally offer the strongest balance of capability, price, and ease of implementation” Qwen 3.7 Flash · direct prompt · first choice
“generally considered to be Apromore, UiPath Process Mining, and ABBYY Timeline” Mistral Small · direct prompt · first choice
“Best Overall for Most Mid-Market Companies: UiPath Process Mining” GLM 4.7 FlashX · paraphrase prompt · first choice

What the models said about ABBYY Timeline

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

“cautionary remarks about Timeline's ability to intuitively gather insights, as well as the number of steps required to do so” Muse Glimmer 30B · negative prompt · soft negative
“noted to be "behind the innovation curve," especially lacking GenAI capabilities” Mistral Small · negative prompt · soft negative
“generally considered to be Apromore, UiPath Process Mining, and ABBYY Timeline” Mistral Small · direct prompt · first choice
“Agile & User-Friendly Mid-Market Vendors: ABBYY Timeline... Faster time-to-value, lower cost, simpler licensing” Gemini 3.5 Flash · scale prompt · alternative
“Choose ABBYY/Appian if you need predictive intelligence or low-code integration” Kimi K2 · comparative prompt · alternative
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.