AnnotateIt
Web app

Comparison

How AnnotateIt compares

Short answer

AnnotateIt is best suited to individual computer vision engineers and researchers who want AI-assisted annotation on their own machine, with no AnnotateIt account or server. Local tools need no upload; optional ChatGPT or Claude sends the attached image and context to the selected provider (OpenAI or Anthropic). If several people label from one shared queue, if open source is a hard requirement, or if you want training and deployment in the same product, one of the tools below is the better answer — and each row here says which.

Six tools, their annotation workflows and architectural trade-offs, without scores. Read the matrix to narrow the field, then open the full comparison of whichever tool you were actually weighing — those pages carry the migration steps, the honest trade-offs and the sources.

Annotate with ChatGPT or Claude

Describe it. Refine it. Review it on the canvas.

Ask for boxes, segmentation polygons or image classes in plain language. Work with one image or video frame in chat, or give Auto-annotate one instruction for a batch of images. Review the results directly in AnnotateIt.

  1. 01

    Ask in context

    Open Annotate with ChatGPT or Claude above Next. The current image or frame is attached by default; you can turn it off.

  2. 02

    Refine together

    Create, rename, recolor or delete project labels with confirmation. Ask follow-up questions to refine pending boxes or polygons.

  3. 03

    Accept or reject

    Review the usual AI suggestions on the canvas. Use the existing Accept / Reject controls; the chat reports when nothing was annotated.

How to annotate with ChatGPT →

OpenAI API and Claude API on web and desktop. ChatGPT via Codex and Claude Code on Windows and macOS require the corresponding installed CLI and account access. Unavailable on native iOS / Android.

Optional online feature: an attached chat message sends one image or one frame and context to your selected provider, OpenAI or Anthropic. Starting an assistant batch sends eligible images and project labels from your chosen scope. No whole-video or keypoint generation. Local AI tools remain separate.

Side by side

AnnotateItCVATRoboflowLabel StudioX-AnyLabelingRectLabel
Chat / prompt annotationChatGPT / Claude → canvas + labelsSAM 3 prompts / AI AgentsAgent + Auto Label / MCPML backends; commercial Prompts / AssistantMultimodal chatbotSAM prompts / Core ML
Where it runsYour deviceOnline or self-hosted serverHosted annotation; cloud / local inferenceSelf-hosted or managed cloudYour deviceYour Mac
AccountNone for local tools; own AI account for chatRequiredRequiredRequiredNone locally; provider access for remote AIStore license; no annotation login
SetupInstall, or a browser tabCloud account or server setupSign upStart a server or use hosted editionRelease or Python envMac App Store
Works offlineLocal tools; chat needs internetConfigured self-hosted setupHosted editor needs networkSelf-hosted onlyLocal workflowYes
AI assistanceLocal models + optional ChatGPT or ClaudeHosted models / Nuclio / agentsAuto Label; browser SAMML backends / commercial AI featuresLocal model zooSAM 3 / SAM 2 / Core ML / OCR
Team workflowsNo — single userAssignments / review / consensusAssignments and reviewEdition-dependent team / review toolsLocal application workflowLocal application workflow
Open sourceNoCommunity: yesHosted editor proprietary; Inference open sourceCommunity: yesYesApplication source not published
Training / production deploymentExperimental external training; no hosted deploymentExternal training integrationsManaged training; cloud / local inferenceConnected ML-backend trainingExternal Ultralytics training / ONNX exportExternal training tutorials; local model use
PlatformsWeb, Windows, macOS, iOSWeb client + serverWebWebWindows, macOS, LinuxmacOS

Rows marked in this column are the ones where AnnotateIt is the weaker choice.

Last reviewed: September 19, 2026

All five named competitors reviewed against official sources. CVAT release baseline: 2.76.0; X-AnyLabeling packaged baseline: 4.0.6. CVAT capabilities and edition differences →

Rows summarize documented workflows and deployment choices. Availability varies by edition, plan, platform and configured integrations; a short cell is not a complete feature inventory. See each detailed comparison and its official sources. No speed or accuracy ranking is implied.

Sources:CVAT 2.76.0 — September 16, 2026CVAT model integration by editionRoboflow deployment optionsRoboflow open-source InferenceLabel Studio edition comparisonLabel Studio ML backend guideX-AnyLabeling 4.0.6 — September 5, 2026X-AnyLabeling 4.0.6 external Ultralytics trainingRectLabel trial, subscription and Pro licenseCVAT AI modelsRoboflow Auto Label and agent workflowLabel Studio AI AssistantX-AnyLabeling 4.0.6 chatbotRectLabel features

Full comparisons

Each page below covers one tool properly: where it wins, where it does not, how to move a dataset across, and the sources behind every row.

When AnnotateIt is the wrong choice

Requirements that call for a different product or additional infrastructure.

  • Several annotators work one shared pool of images with assignment and review — there is no server, no locking and no merge. Use CVAT.
  • Auditable source is a hard requirement. The public GitHub organisation hosts the issue tracker and the roadmap, not the application. Use CVAT, Label Studio or X-AnyLabeling.
  • You want managed cloud training and a deployed endpoint. AnnotateIt has local model evaluation and an experimental connected runner, but does not provide that hosted infrastructure. Consider Roboflow.
  • Your work is not computer vision — text, audio, documents, time series. Use Label Studio.

By situation, not by product

Some readers are not choosing between two named tools — they have a constraint. These pages start from the constraint instead.

Open AnnotateIt in your browser

Create your first local project in the browser. Optional ChatGPT or Claude annotation needs your own AI connection.

Open web appGet the native apps

Questions before you start?Contact support →

Video tutorial

AnnotateIt tutorial