Data as of Aug 25, 2026 · Based on 5,367 AI responses · See how Parse measures this
Data Annotation Platforms and Services
Parse
https://parse.gl
now leads AI recommendations for data annotation, frequently cited for its enterprise-grade workflows and team management capabilities. While open-source tools like remain go-to options for affordable projects, the most significant trend is the growing prominence of comprehensive enterprise platforms and the rapid emergence of for large-, managed annotation.
| # | Brand | What AI says | Mention rate |
|---|---|---|---|
| 1 | Enterprise-grade platform for managing large teams and complex annotation workflows. | 54% | |
| 2 | The top-recommended free, open-source tool for computer vision and video annotation. | 49% | |
| 3 | Cited for computer vision projects, team collaboration, and AI-assisted workflows. | 44% | |
| 4 | Recommended for complex video, multimodal, and enterprise-grade data projects. | 38% | |
| 5 | A flexible, open-source choice, especially favored for NLP and multimodal projects. | 35% | |
| 6 | Noted for AI-powered 'Auto-Annotate' features for high-precision segmentation tasks. | 25% | |
| 7 | A rapidly rising recommendation for large-scale, managed annotation services. | 22% | |
| 8 | Popular developer-friendly tool integrating annotation with the full model training pipeline. | 21% | |
| 9 | 16% | ||
| 10 | 14% | ||
| 11 | Frequently cited service for medical imaging using certified radiologists. | 12% | |
| 12 | 11% | ||
| 13 | 11% | ||
| 14 | 9% | ||
| 15 | 8% | ||
| 16 | 7% | ||
| 17 | 6% | ||
| 18 | 6% | ||
| 19 | 6% | ||
| 20 | 5% | ||
| 21 | 5% | ||
| 22 | 4% | ||
| 23 | 4% | ||
| 24 | 4% | ||
| 25 | 4% |
Shifted from the overall #1 spot to being a top specialist for free video annotation tasks.
Grew from a mid-tier option to a top-two recommendation in many prompts by early 2026.
Emerged as a top recommendation for high-volume enterprise projects after November 2025.
“An option for providing a managed workforce.” → “An industry leader for high-volume, enterprise-grade labeling.”
Who wins on each AI
The same market, seen by two models.
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
| 66% | 55% | ||
| 60% | 52% | ||
| 47% | 48% | ||
| 51% | 23% | ||
| 45% | 43% |
The two models disagree most about Segment Anything Model 2 (ChatGPT #23, Google #12) and V7 Darwin (ChatGPT #9, Google #20).
Sources AI cited
medium.com is the page AI reaches for most here, cited in 35% of analyzed answers.
Share of supported contexts
share of answers
Labelbox now leads AI recommendations for data annotation, frequently cited for its enterprise-grade workflows and team management capabilities. While open-source tools like CVAT remain go-to options for affordable projects, the most significant trend is the growing prominence of comprehensive enterprise platforms and the rapid emergence of Scale for large-scale, managed annotation.
Across 5,367 AI responses, Labelbox is mentioned most, named in 54% of them, followed by CVAT (49%) and SuperAnnotate (44%).
Parse measures each brand's mention rate — the share of answers naming it — across 5,367 AI responses to this market's buyer questions. Answers are collected daily and the ranking is published weekly.
Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.
AI responses initially gave significant weight to the open-source tool CVAT, but from December 2025 onwards, the consensus shifted strongly towards enterprise platforms.
Labelbox and
SuperAnnotate became the most frequent recommendations, with
Scale and also appearing as top-tier options for large- projects.
AI responses initially gave significant weight to the open-source tool CVAT, but from December 2025 onwards, the consensus shifted strongly towards enterprise platforms.
Labelbox and
SuperAnnotate became the most frequent recommendations, with and also appearing as top-tier options for large- projects.
Across the entire period, AI assistants consistently recommended the open-source tools CVAT and as the best affordable options. Since early 2026, gained significant traction as a developer-friendly choice with a generous free tier and AI-assisted features.
share of answers
Brands mentioned
Brands mentioned
Across the entire period, AI assistants consistently recommended the open-source tools CVAT and
Label Studio as the best affordable options. Since early 2026,
Roboflow gained significant traction as a developer-friendly choice with a generous free tier and AI-assisted features.
The market map