Labellerr and Roboflow

Roboflow labels faster than Labellerr, then trains and deploys your model

Auto Label does the first pass from a text prompt, your own trained model does the next, and the same platform trains and deploys the result. Every plan, including Free, comes with self-hosted inference, model weights download, and a private workspace. Over 2 million engineers build with Roboflow.

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AI system detecting mold on strawberries in plastic containers on a conveyor belt.

Why are companies choosing Roboflow?

Roboflow is enterprise vision AI infrastructure, used by more than half of the Fortune 100, with SOC 2 Type II, HIPAA, and air-gapped deployment. The AI labeling tool that keeps going: label, train, deploy, and improve in one platform.

  • AI labeling, out of the box

    Auto Label labels a whole dataset from a text prompt and Smart Polygon makes masks in one click, with no labeling credits to track.

  • Faster every round

    Label Assist pre-annotates new images with the model you just trained, so each labeling pass takes less time than the last.

  • From labels to production

    Train RF-DETR or YOLO26 in one click and deploy to the cloud, the edge, or your own hardware, no ML background needed.

  • Roboflow Annotate labeling cans with AI box prompting

    Fast data labeling

    Label data quickly with a suite of AI-assisted annotation tools to augment human labeling or fully automate your data labeling pipeline.

  • Workflow blocks for notifications and integrations

    Build vision AI applications with ease

    Use a low-code open source platform to simplify building and deploying vision AI applications.

  • A team reviewing a detected pallet in a warehouse aisle

    Machine learning expertise, always

    Work with account-dedicated AI specialists and Field Engineers to accelerate development and optimize performance.

  • Photos from datasets across industries

    Datasets and models for every industry

    Access thousands of datasets and pre-trained models to kickstart your computer vision projects.

  • Logos of OpenAI, Microsoft, Meta, Anthropic, Google and Qwen

    Flexible model licensing

    Choose from a range of licensing options to fit your needs, whether for commercial use, private deployment, or collaboration across teams.

Want to move from Labellerr to Roboflow?

  • Import images to Roboflow

    Bring COCO, YOLO, or Pascal VOC exports from Labellerr into Roboflow for model training.

  • Train and deploy

    Train on your imported labels in one click, then deploy to the cloud, a Jetson, or an air-gapped server.

  • Automate data labeling

    Use AI labeling in Roboflow to automate 90% of human labeling.

OK I’m ready, how do I use Roboflow?

Roboflow makes it easy to build, train, and deploy custom computer vision models, even if you’re not a machine learning expert.

Start a free Roboflow account

Talk to a Vision AI engineer about labeling, training, and deploying in one place

Bring us your Labellerr project and we'll map the path to a deployed model on the first call.

Ask us about:

  • Import of your existing labels in COCO, YOLO, or 40+ other formats
  • A live demo of Auto Label on your own images
  • Training on current architectures, including RF-DETR
  • Deployment options: cloud, VPC, on-prem, edge, or air-gapped

Over 80,000 organizations build with Roboflow.

  • Rivian
  • Pella
  • Chobani
  • USG Corporation
  • BNSF Railway
  • American Woodmark
Start where you are

Compare Labellerr and Roboflow

With Roboflow, your trained model can become a labeling assistant for the next batch of images. That connection is central to the difference with Labellerr. Labellerr offers AI-assisted annotation, quality review, and managed labeling services across multiple data types, with exports and an SDK for your ML pipeline. Roboflow includes model training and production deployment alongside those dataset workflows.

Start with Auto Label (opens in a new tab), drafting annotations from a text prompt describing your classes. Review the results, create a dataset version, and train a specialized model such as RF-DETR or YOLO. Then use that model with Label Assist to suggest annotations on new images. Your team can correct its mistakes and add those examples to the next training version, building on the work it has already done.

The model can then become part of a running application. Roboflow Agent helps choose models and build Workflows that connect predictions to application logic and downstream systems. Through the ChatGPT plugin (opens in a new tab) and MCP integration, engineers can also prepare datasets, launch labeling jobs, train models, and test inference from their existing tools. Deploy to a hosted endpoint or run supported models and Workflows on your own hardware.

You can try this cycle with private images on Roboflow’s free plan, which includes 10 monthly credits and supported model weight downloads. Self-hosted inference does not consume Roboflow credits. Teams choose Roboflow when they want their labeling investment to support the whole application, from the first training set to the production examples that improve the next model.

Labellerr vs Roboflow Annotate: Feature by Feature

FeatureRoboflow AnnotateLabellerr
Supported labeling tasksObject detection, segmentation, classification, keypoint, multimodalObject detection, polygon and polyline, semantic and instance segmentation, classification, keypoints, OCR, captioning, plus text, audio, PDF, and DICOM
Video labelingYesYes, SAM 2 object tracking and event tagging
Running environmentWeb browser, no installWeb browser, hosted cloud
Free tierYes, 10 credits a month (AI labeling uses credits), with free self-hosted inference, model weights download, and a private workspaceLimited, Researcher tier with 2,500 data credits and one seat
Open sourceYes, open-source supervision and inference libraries that run alongside the Roboflow platformNo; GitHub holds tutorials and SAM forks, not the platform
Hosted labeling environmentYesYes
AI auto labelingYes, Auto Label labels images from a text prompt; 1,000 images in under ten minutesYes, SAM 3 text prompts, LabelGPT zero-shot prompting, and active-learning auto-label jobs (Pro and above)
Label assist with foundation modelsYes, Smart Polygon powered by Segment AnythingYes, SAM, SAM 2, and SAM 3
Label assist with custom modelsYes, Label Assist pre-annotates with any model trained or uploaded to Roboflow, so labeling gets faster every training runPartial, upload pre-annotations from your own model; no hosted custom-model assistant
Dataset managementYes, versioning, train/valid/test splits, health check, preprocessingBasic, datasets and projects with S3 and GCS connectors
Semantic dataset searchYesAttribute-based filtering (added May 2026)
Dataset analyticsYesLimited
Labeling analyticsYesYes, annotator productivity and review dashboards
Labeling historyYesReview and accept/reject workflow; full version history not documented
Image augmentationYesNo
Export formats40+ formatsJSON, COCO, YOLO, Pascal VOC, CSV, custom schemas
Role-based access controlYesYes
SSOYesEnterprise only
Python SDK / APIYes, SDK on PyPI plus REST APIYes, REST API with OpenAPI spec; SDK installs from GitHub rather than PyPI
Model trainingYes, RF-DETR, YOLO (v8 / v11 / v26), and more, trained from the labeled dataset in one stepNo
Model deploymentYes, hosted, edge, or self-hostedNo
Vision sub-agents for frontier models (MCP)Yes, trained models are exposed over MCP so frontier models can call them as specialized vision toolsNo
Application builderYes, Roboflow WorkflowsNo
Managed labeling workforceVia Roboflow partnersYes, from $6 per hour
Self-hosted inference serverYes, open-source inference server for custom and foundation modelsNo, native hosted inference and deployment are not documented
Open-source CV libraryYes, supervision for detections, tracking, annotation, and evaluationNo; the GitHub organization holds tutorials and forks of SAM 2 and SAM 3 inference code
Open-source CV integrationsYes, Hugging Face Transformers, MMDetection, and the broader open-source CV stackNo documented Hugging Face, MLflow, or Databricks integrations; connectors for AWS S3 and Google Cloud Storage
ComplianceSOC 2 Type II, HIPAA with BAAs, and PCI DSSSOC 2 Type II and GDPR claimed; HIPAA not claimed and ISO 27001 not documented

Best Labellerr Alternatives

Roboflow is the top Labellerr alternative for teams that want labeling, training, and deployment in one platform. Teams comparing Labellerr also look at: