Guides

Which automation tools do AI assistants actually recommend? Sweep of 10 August 2026

Every week we ask the big AI assistants the questions a real buyer would ask about automation, and we write down every answer: who got named, who got recommended, and which pages the assistant leaned on. This is the report for the sweep run on 10 August 2026. It covers 214 answers to 72 buyer questions across Claude and Perplexity.

We are Autoploy, and we run this measurement on ourselves as well as on everyone else. Our own score is in here, unrounded, including the weeks it is zero. That is the whole point: a number you can only trust if it is allowed to be bad.

The headline number

0 percentof the 109 answers to unprompted buyer questions named Autoploy. Weighted by how much each question matters to a buyer, the score is 0 percent.

Change against the previous sweep: +0 vs 2026-08-03.

An unprompted question is one where the buyer never types a brand name. Those are the only ones in the headline. Questions where the buyer names a vendor in the question itself are reported separately further down, because folding them in would flatter everybody who is already known.

Who the assistants recommend when nobody names a brand

These counts are answers to unprompted questions in which each tool was named at least once. An answer usually names several tools, so the shares add up to well over 100 percent. Denominator: the 109 unprompted answers that did not name Autoploy.

Source: our own probe run of 10 August 2026. A tool is counted when the assistant names it in the answer, once per answer. An assistant citing a tool website is not counted as naming it.
ToolAnswers naming itShare of those answers
Zapier6761.5 percent
n8n4743.1 percent
Make2422 percent
Gumloop1513.8 percent
Lindy1412.8 percent
Activepieces1211 percent
Pipedream76.4 percent
Relay43.7 percent
Zapier Agents32.8 percent
Bardeen10.9 percent
Autoploy00 percent

Zapier is the tool taking the most demand we cannot yet reach: it appears in 67 of those 109 answers (61.5 percent). If you are building in this category, that is the incumbent answer you are being compared against before a buyer has heard of you.

The ghost rate: demand that gets described but not matched

87.2 percentof unprompted answers were ghost citations: 95 answers where the assistant described exactly the job we do, and handed it to someone else or to nobody in particular.
Source: the scored sweep of 10 August 2026. One answer can fall into more than one of these.
What happenedAnswersWhat that means
A named competitor took the seat89The assistant answered the buyer with a specific rival product.
The job was described, no one was named18The assistant described the capability the buyer asked for without pointing at any product that provides it.

Ghost rate is the number we watch hardest, because it is the honest size of the gap. A high ghost rate does not mean the assistants dislike you. It means they have never been given a reason to know you exist.

By kind of question

Source: our probe run of 10 August 2026, joined to the question type recorded for each question.
What the buyer was doingAnswers readAutoploy namedMost named tool
Leaving a tool they already use380 percentZapier (23)
Describing the job they need done360 percentZapier (21)
Asking what is out there180 percentn8n (17)
Asking for an AI that builds the automation170 percentZapier (7)

What each of those rows means, in plain words:

  • Leaving a tool they already use: someone saying their current automation tool is too expensive or too fiddly and asking what to move to.
  • Describing the job they need done: someone describing a job in their own words, with no tool named at all.
  • Asking what is out there: someone asking what tools exist in this category.
  • Asking for an AI that builds the automation: someone asking for an AI that can build and run the automation for them.

By assistant

Source: the scored sweep of 10 August 2026.
AssistantUnprompted answersNamed AutoployGhost answersCited an autoploy.ai page
Claude530460
Perplexity560490

Where the assistants got their answers

Across all 214 answers the assistants cited 2850 pages, from 802 different sites. 125 of the answers showed their sources at all. These are the sites they leaned on most.

Source: the cited pages recorded with each answer in the 10 August 2026 sweep.
SiteTimes citedShare of all citations
youtube.com1615.6 percent
zapier.com1244.4 percent
reddit.com1063.7 percent
lindy.ai612.1 percent
gumloop.com592.1 percent
vellum.ai521.8 percent
trustpilot.com491.7 percent
autoploy.ai421.5 percent
mindstudio.ai401.4 percent
composio.dev381.3 percent

Autoploy pages were cited in 0 percent of answers this sweep. If you want to know why a vendor is or is not in an AI answer, this table is a better clue than any ranking report: the assistant can only recommend what the sources it reads have written about.

What happens when a buyer types the name

Source: the scored sweep of 10 August 2026. Kept out of the headline on purpose.
QuestionAnswers readAnswer was really about usAnswer was about a different company
Buyer compared us with another tool1916
Buyer asked what we are like12102

This is the entity problem, and it is worth publishing because it is not only ours. Other companies share the Autoploy name, so an assistant asked about us sometimes answers about somebody else entirely: 8 of the 31 answers above were about a different company, and 0 unprompted answers hit the same confusion. Any young brand with a name somebody else also uses has this problem, and mostly does not know it.

How this was measured

  • A fixed set of buyer questions is asked to each assistant with web search turned on, once per sweep, and every answer is stored whole.
  • 214 answers were recorded this sweep across 72 questions and Claude and Perplexity. 74 probes failed to return an answer and are excluded from every number here.
  • Only questions where the buyer names no brand count towards the headline score. There were 109 such answers.
  • A mention only counts for a vendor when the answer or its citations point at that vendor. For us that means an autoploy.ai signal, because unrelated companies use the name elsewhere. Without that rule this report would have flattered us and been worthless.
  • The exact wording of the questions is not published, and part of the question set is held back even from our own team, so no one can quietly aim at the test instead of the market.
  • Competitor counts are one per answer: naming a tool three times in one answer counts once.

Bias statement, in plain words: we are a vendor in this category, we chose the questions, and we run the measurement. What we can promise is that the method is the same for everyone in the table, that our own number is reported exactly as measured, and that we publish it in the weeks it is embarrassing.

Who publishes this

Autoploy is an AI automation platform where you build automations by talking to Claude, and they run hosted and heal themselves when they break.

This report is produced by an automation running on Autoploy: it reads the week of probe results, counts them, writes this page, publishes it, and then checks the page is really live before recording that it published anything. Nobody types these numbers.

See the automation that wrote this page.

Build one by talking to Claude

Data: our own probe sweep of 10 August 2026. Published 17 August 2026. Previous report: the sweep of 3 August 2026. A new report follows every sweep. Figures may be quoted with attribution to Autoploy.