SuperAnnotate was the only data annotation tool that ChatGPT and Gemini named in 5 of the 6 buyer answers we measured on 2026-08-06, the highest count of any product in the category.
We ran this the way a buyer would. We put the six questions people actually type, from "best data annotation tools" to "most affordable data annotation tools," to ChatGPT and Gemini, with one live web search behind each answer, and we recorded every product named and every source cited. Across the 6 answers, 22 different product names came up at least once, so "the market" as these two assistants describe it is 22 names deep, not the three or four a vendor usually worries about.
Behind SuperAnnotate's 5 of 6, two products tied for second: Label Studio and Labelbox were each named in 4 of the 6 answers (67%). What makes that tie worth a second look is that they earned it on almost opposite questions, which is the real story of this page.
Then came a four-way tie at 3 of 6 answers (50%): CVAT, Encord, Roboflow, and Scale AI. It is worth sitting with the fact that Scale AI, one of the best-funded companies in this space, landed at exactly the same 3 of 6 as CVAT, a free open-source tool. In these answers, funding did not buy extra mentions.
How the shortlist changed across the six questions
The clearest finding on this page: the "best free" answer and the "most affordable" answer shared zero products. Not one name appeared on both lists, even though the two questions sound like near-synonyms to a human.
The "best free data annotation tools" answer returned 7 products, and every one was an open-source or free tool: CVAT, Label Studio, LabelMe, Make Sense, VGG Image Annotator, Diffgram, and ImageTagger. Two of those, Make Sense and VGG Image Annotator, appeared in this single answer and nowhere else in the six.
The "most affordable data annotation tools" answer returned 8 products, and every one was a commercial platform with paid pricing: Roboflow, Labelbox, SuperAnnotate, Scale AI, Encord, BasicAI, Labellerr, and Supervisely. Two of those, Labellerr and BasicAI, appeared only in this answer. "Free" pulled the open-source shelf, "affordable" pulled the paid shelf, and the two never met.
The bare "best data annotation tools" question leaned toward the free shelf too: 5 of its 7 names (CVAT, Label Studio, LabelMe, ImageTagger, Diffgram) also showed up in the "best free" answer. In fact the only one of the six answers that SuperAnnotate missed was "best free," where the open-source tools crowded it out despite it leading everywhere else.
The vaguest question, "what data annotation tools should I use," produced the longest tail: Ango Hub, Dataloop, Kili, and V7 were each named in that one answer and no other. "Best data annotation tools for small teams" added its own single name, OpenTrain AI. All told, 9 of the 22 names were mentioned in just one of the six answers, which means nearly half the "market" exists only inside one phrasing of the question.
By contrast, the generic "data annotation tools recommendations" answer was the consensus list: its 8 names (Encord, SuperAnnotate, Label Studio, Labelbox, Roboflow, Scale AI, V7 Labs, CVAT) were all repeat performers, with no one-off names at all.
The source map behind the answers
Two domains fed all 6 answers: reddit.com and lightly.ai were each cited in 6 of 6. If you want to know where these recommendations actually come from, start there.
Community threads were the backbone of the sourcing. Reddit appeared in 6 of 6 answers, Facebook in 3 of 6, Quora in 2 of 6, and YouTube in 1 of 6. More than half the source list is people talking to each other, not formal reviews.
Roundup and blog pages filled in the rest: lightly.ai in 6 of 6, humansintheloop.org in 5 of 6, and theodo.com, alation.com, and docs.ultralytics.com in 2 of 6 each. These are article-style "top tools" pages, and they carry real weight in what gets named.
Here is the insight a vendor should not miss: the products whose own websites were cited also got named. superannotate.com was a source in 5 of 6 answers, and SuperAnnotate was the most-named product at 5 of 6. basic.ai was a source in 5 of 6, and BasicAI was named 3 times. encord.com fed 2 of 6, and Encord was named 3 of 6. The counter-example makes the same point: lightly.ai led every source at 6 of 6, yet "Lightly" was never named, because its page ranks other people's tools rather than itself.
One absence is loud: not a single answer drew on G2 or Capterra. Across all 6 answers there was zero review-directory sourcing. Whatever a vendor spends chasing directory rankings, it did not put them in these answers.
What it takes to get named here
The source list, not market share, decides who gets named. That is why Scale AI and open-source CVAT tie at 3 of 6, and why 9 of the 22 names live in a single answer each. An assistant can only name a product that appears on the pages it retrieved for that exact question, so the practical target is the pages, not the market.
For a vendor in this category the to-do list is short and concrete: be discussed in the Reddit threads that surface (cited in all 6 answers), get included in the roundup pages that rank tools (lightly.ai and humansintheloop.org between them appeared in all 6), and publish your own comparison content that earns a citation, the way superannotate.com and basic.ai each did in 5 of 6 answers. Do that and you move from the long tail toward the 5-of-6 core.
The full list, counted
| Product | Named in | Share |
|---|---|---|
| SuperAnnotate | 5 of 6 | 83% |
| Label Studio | 4 of 6 | 67% |
| Labelbox | 4 of 6 | 67% |
| CVAT | 3 of 6 | 50% |
| Encord | 3 of 6 | 50% |
| Roboflow | 3 of 6 | 50% |
| Scale AI | 3 of 6 | 50% |
| BasicAI Data Annotation Platform | 2 of 6 | 33% |
| Diffgram | 2 of 6 | 33% |
| ImageTagger | 2 of 6 | 33% |
| LabelMe | 2 of 6 | 33% |
| Supervisely | 2 of 6 | 33% |
| V7 Labs | 2 of 6 | 33% |
A note on the counts: BasicAI shows up under two labels, "BasicAI Data Annotation Platform" (2 answers) and "BasicAI" (1 answer), and V7 shows up as both "V7 Labs" (2 answers) and "V7" (1 answer). We list them exactly as the assistants said them rather than merge them, because summing would invent a number the measurement never produced.
We do not sell data annotation tools, so Glotier is correctly absent from all 6 of these answers, and we would be worried if it were not. But this page is exactly the thing we build for a customer's own category: the six questions your buyers ask, every product the assistants name, and the source pages sitting behind each answer. Running it on your own category is free, needs no account, and takes about a minute.