How is the ranking calculated?

One score out of 100, weighted by execution 35%, reliability 15%, ready to use 15%, autonomy 35%. Documented support earns one point, partial support half, and no support zero. Unknown evidence is excluded from the score denominator, with a separate research-completeness gate for awards. Execution and reliability describe documented features, not measured task-success rates or uptime.

Does AI visibility determine the winner?

No. The default order comes from the product score. Attention is measured separately using 100 neutral category-specific prompts across ChatGPT, Claude, Gemini and Google AI Overviews. Funding informs the attention verdict, never the product score.

What does overhyped mean here?

A product the market talks about far more than its score justifies, once the money behind it is accounted for. Attention and score are each converted to a position in the tracked field, a brand's disclosed funding is charged against its attention by up to 25 points, and anything still at least 15 points louder than it scores is called overhyped. A tool with almost no measured mentions never is: it is not loud, it is unmeasured.

What does underrated mean here?

The mirror of overhyped: a product that stands at least 15 points higher on the score than on attention once funding is charged against it, and that was named in at least one tracked answer. A tool that appeared in none is under the radar rather than underrated, because there is no attention to judge it against yet. Underrated is the finding the page exists for (a product doing the work without the volume behind it), and it is the only verdict a tool can earn by being good rather than by being loud.

Free AI automation ranking

The best AI automation platforms

28 AI automation platforms compared for hands-off work: what they can execute, how independently they run, their reliability controls, and how much setup they need.

Last measured 31 August 2026

This month's results

Our pick

Notis for hands-off work

The top 3

The highest-scoring award-eligible products. Rank badges match the full table.

Gold#1

Zapier

Strongest on reliability

98.3/ 100

Overall score

Silver#2

Activepieces

Strongest on execution

97.5/ 100

Overall score

Bronze#3

Make

Strongest on execution

93.9/ 100

Overall score

Podium and bonus awards require at least 90% of the category matrix checked, at least 80% of every scored feature group checked, and a known setup level. Other scores are provisional. Unknown is not treated as no.

Bonus awards

Picks and standouts beyond the overall score. Attention combines visibility in AI answers with audience reach; gap awards also account for funding.

Our pick for hands-off work

Notis

For delegating everyday tasks in plain language, without building workflows step by step.

Overall score: 75.7 / 100 · #12 of 28

More attention than score

Lindy

The largest gap where attention outpaces the product score, after accounting for funding.

Score rank: #17 of 28 · Attention rank: #4

The ranking

Every tracked product by score, next to its documented capabilities, measured attention and disclosed funding. Sort or filter the table to explore the field. Provisional scores remain visible but cannot win awards.

Show

26 of 28 tracked platforms.

AI automation platforms ranked by the overall score, with the places each has moved since last week, documented capability, measured attention, disclosed funding, the movement on each since the last measurement and the verdict. Sortable by capability, attention or funding.
#	Platform				Verdict
1	Zapier Workflow automation platform	95—	67—	$1M—	Earns it
2	Activepieces AI workflow automation platform	100—	12.3—	Undisclosed—	Earns it
3	Make Visual AI automation platform	100—	35.8—	Bootstrapped—	Earns it
4	Wordware AI assistant with a companion workflow-automation builder	85—	0—	$30M—	Under the radar
5	Base44 No-code app builder with scheduled/triggered workflow automation and an autonomous cross-tool AI agent (Superagent)	70—	0.4—	Bootstrapped—	Earns it
6	Notion AI AI workspace assistant and automation platform	75—	0.7—	$343M—	Earns it
7	Duckie AI customer-support agent platform	65—	0—	Undisclosed—	Under the radar
8	Vellum Personal AI assistant	60—	0.7—	$25M—	Earns it
9	Tasklet Cloud AI agent platform for teams	85—	0—	$42M—	Under the radar
10	OpenClaw Open-source self-hosted personal AI agent	75—	0—	Undisclosed—	Under the radar
11	Duet Cloud AI coworker for recurring operations and internal app building	50—	0—	$5M—	Under the radar
12	Notis Personal AI assistant	55—	0—	Bootstrapped—	Under the radar
13	Town AI work assistant ("Townie") with built-in routine automation	70—	0—	$73M—	Under the radar
14	Junior AI employee and AI coworker platform	55—	0—	Undisclosed—	Under the radar
15	Squad AI teammate and workflow automation platform	65—	0—	Undisclosed—	Under the radar
16	Workmate Managed AI agent workforce	63—	0—	Undisclosed—	Under the radar
17	Lindy Slack-native AI teammate	40—	3.6—	$50M—	Overhyped
18	Cofounder Agent-native company operating system	35—	0—	$9M—	Under the radar
19	Context Enterprise AI agent platform	30—	0.4—	$16M—	Earns it
20	Paperclip Open-source AI agent workforce orchestration platform	44—	0—	Undisclosed—	Under the radar

Score = execution 35%, reliability 15%, ready to use 15%, autonomy 35%. How each component is measured.

Browse all 28 profiles

Loud is not the same as capable

One chart, one line. Up is where a product stands on the score. Across is its measured AI-answer attention, adjusted for the money behind it, because money buys attention and a bootstrapped brand at the same volume has proved something a funded one has not. On the line, the attention is earned. The interesting ones are the distance off it.

Tracked productShut down or acquired

Both axes are a tool's position in the tracked field rather than its raw number, because a weighted score out of 100 and a long-tail attention measure cannot be subtracted from each other. Across is measured AI-answer attention plus the premium its funding explains, added to attention rather than taken off the score. Above the dashed diagonal a product is better than it is talked about; below it, the reverse. The shaded corridor is within 15 percentile points of the line, which is close enough to call even. The 10 platforms stacked at the left appeared in no tracked answer, raised nothing we could verify, so there is no signal left to tell them apart. They share a position because they share the measurement, and fanning them would invent an order. Every point is a row in the table above.

Does money buy attention?

The same field, split the other way: disclosed funding against measured attention. The dashed line is fitted to the products with known funding in this category; the distance from it shows which brands get more or less attention than that relationship suggests. Unknown funding is shown separately, not treated as zero.

Tracked productShut down or acquiredThe dashed line is the trend this month's field shows; the band is one standard deviation around it. The vertical axis is a square root, so the crowd under 5 stays readable next to the two brands above 30. The money axis stops at the decade that covers the field; a brand that has raised more is pinned to the right edge with a chevron and its real total, rather than stretching the axis until everyone else touches. Bootstrapped and undisclosed brands sit outside the model (a log axis has no zero, and an undisclosed round has no number), so they are fenced off at the left rather than dropped.

How the score is calculated

Every product is scored for hands-off work using the same documented feature evidence and weights.

35%Execution: Documented ability to act across apps, browsers and workflows, including branches, loops, data transforms and code. This is feature evidence, not a task-success benchmark.
15%Reliability: Documented approvals, error handling, logs, testing, versioning, monitoring and secret management. This measures available controls, not observed uptime.
15%Ready to use: Whether you can sign up and start, need some setup, or must operate the platform yourself.
35%Autonomy: Natural-language building, schedules, app-event triggers, long-running workflows, AI steps, agents and knowledge retrieval.

Comparable research before awards

Provisional products remain in the full score-sorted table, clearly labelled. Rank badges on the podium retain their positions in that table.

Score ordering

Method hands-off-v2. Exact score ties break on autonomy, then execution, then slug. Popularity and funding never break a score tie.

Money raised, charged against attention

Attention is measured monthly, converted to a position in the tracked field, and then charged for the money behind it (up to 25 points, log-scaled and capped) before the field is ranked again on the result.

Money buys attention. A bootstrapped brand talked about as much as a funded one has proved something the funded one has not.

Overhyped and underrated are what is left: the distance between where a tool ranks on the score and where it ranks on attention after that charge. It is one number, and it is the one the quadrant above plots, so the picture and the verdict are the same claim. The chart beside it shows the relationship the charge is drawn from.

The prompt panel

100 neutral prompts per category, fixed for the month, run through DataForSEO across ChatGPT, Claude, Gemini and Google AI Overviews, for 400 answers per product. Each brand comes back as AI answer visibility and share of voice, which is the whole of its attention score.

A tool named in none of them scores zero on the panel. That is a finding about these 100 questions, not about the tool. A Google result with no AI Overview is a measured absence; a provider failure is unmeasured and blocks the whole month.

Each tool's own page lists the questions it appears in and its position on every one, so a score can be checked rather than trusted.

The capability matrix behind every score is open, cell by cell, in the AI automation platforms comparison directory.

Questions people ask about this ranking

How is the ranking calculated?: One score out of 100, weighted by execution 35%, reliability 15%, ready to use 15%, autonomy 35%. Documented support earns one point, partial support half, and no support zero. Unknown evidence is excluded from the score denominator, with a separate research-completeness gate for awards. Execution and reliability describe documented features, not measured task-success rates or uptime.
Why is a score marked provisional?: Podium and bonus awards require at least 90% of the category matrix checked, at least 80% of every scored feature group checked, and a known setup level. Other scores are provisional. Unknown is not treated as no.
Does AI visibility determine the winner?: No. The default order comes from the product score. Attention is measured separately using 100 neutral category-specific prompts across ChatGPT, Claude, Gemini and Google AI Overviews. Funding informs the attention verdict, never the product score.
What does overhyped mean here?: A product the market talks about far more than its score justifies, once the money behind it is accounted for. Attention and score are each converted to a position in the tracked field, a brand's disclosed funding is charged against its attention by up to 25 points, and anything still at least 15 points louder than it scores is called overhyped. A tool with almost no measured mentions never is: it is not loud, it is unmeasured.
What does underrated mean here?: The mirror of overhyped: a product that stands at least 15 points higher on the score than on attention once funding is charged against it, and that was named in at least one tracked answer. A tool that appeared in none is under the radar rather than underrated, because there is no attention to judge it against yet. Underrated is the finding the page exists for (a product doing the work without the volume behind it), and it is the only verdict a tool can earn by being good rather than by being loud.

Spotted something out of date?

We check capabilities against dated sources, including vendor documentation and hands-on reviews. Tell us what changed, or which tool we are missing.

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