Labellerr Review
Labellerr offers aggressive pricing and bold speed claims that make it worth evaluating, but verify those 99x faster benchmarks against your specific use case before committing.
What is Labellerr?
Labellerr is an AI-powered annotation platform that competes on price transparency and speed claims. While larger players like Labelbox require sales conversations for pricing, Labellerr publishes their tiers: free for researchers, $9,999/year for Pro teams. They claim 99x faster labeling with 99% accuracy — aggressive numbers that warrant verification against your specific use case.
The platform includes SAM and SAM 2 integration for AI-assisted segmentation, active learning to prioritize valuable samples, and SDK integration for pipeline automation. They support images, video, text, audio, and PDFs, with medical formats (DICOM, LiDAR) on Enterprise. The 14-day pilot with no minimum data commitment makes it low-risk to evaluate. For small teams frustrated by 'contact sales' pricing elsewhere, Labellerr's transparency is refreshing — just approach the marketing claims with appropriate skepticism.
Key Features
- ✓ Free Researcher tier: 2,500 data credits, 1 seat, 100 projects
- ✓ SAM and SAM 2 integration for AI-assisted segmentation
- ✓ SDK integration for ML pipeline automation
- ✓ Active learning workflows to prioritize high-value samples
- ✓ Pre-annotation upload and refinement
- ✓ Export formats: CSV, JSON, COCO, Pascal VOC
- ✓ Annotation services: 1,000+ expert annotators from $6/hour
- ✓ DICOM and medical imaging support on Enterprise tier
Pros & Cons
Pros
- + Transparent pricing: Pro at $9,999/year is clear compared to 'contact sales' competitors
- + Free Researcher tier genuinely useful for students and small experiments
- + SAM/SAM 2 integration for fast AI-assisted segmentation
- + No minimum data commitment — start with a 14-day pilot
- + Managed annotation services available from $6/hour
- + Multi-format support including medical (DICOM) on Enterprise
Cons
- − 99x faster claims need verification — aggressive marketing language
- − Smaller company with less track record than Labelbox or Scale
- − Free tier limited to 2,500 credits and basic file types
- − DICOM/LiDAR/NIfTI only on Enterprise tier
- − Credits don't carry forward monthly on volume pricing
Pricing
Pricing model: Freemium
Who Is Labellerr Best For?
Labellerr targets small teams and researchers who want transparent pricing without enterprise sales cycles. The free Researcher tier is genuinely useful for academic projects and experiments. The Pro plan at $9,999/year with 10 seats is competitively priced for small businesses under 50 employees. It's a good option if you want to know costs upfront rather than negotiate custom quotes. It's less suited for large enterprises (Labelbox or Scale have more track record), teams needing DICOM/medical on day one (requires Enterprise), or projects where the 99x speed claims are critical to your ROI calculation — verify those benchmarks first.
Frequently Asked Questions
Is Labellerr free?
What data types does Labellerr support?
Is Labellerr really 99x faster?
How does Labellerr compare to Labelbox?
Does Labellerr offer annotation services?
What is Labellerr's data credit system?
Alternatives to Labellerr
Enterprise teams needing high-volume, multi-language labeling with managed workforce
Computer vision teams wanting fast AI-assisted annotation with training and deployment built in
Frontier AI labs and enterprises needing LLM training data, RLHF, or autonomous vehicle annotation at scale
Teams needing AI-assisted annotation for images, video, or medical imaging with compliance requirements
Teams needing multimodal annotation with a strong free tier and path to enterprise scale
Computer vision teams wanting open-source flexibility with optional managed cloud hosting
Enterprise teams building production AI pipelines who need annotation, model training, and deployment in one platform
Teams needing multi-modal annotation flexibility who can invest time in template configuration
Computer vision teams needing specialized support for medical imaging, LiDAR, or 3D data with built-in AI models
Autonomous vehicle and robotics teams needing LiDAR annotation with integrated multi-sensor calibration
Enterprise teams deploying production LLMs who need human-in-the-loop evaluation and hallucination detection
AWS-native ML teams who want a managed labeling service integrated with SageMaker training pipelines
Computer vision teams who want AI-assisted annotation combined with optional managed workforce services
Enterprise teams needing multimodal annotation with strong compliance, custom workflows, and optional managed labeling services
Enterprise teams building physical AI (robotics, autonomous vehicles) or medical AI who need multimodal annotation with 3D/LiDAR and DICOM support
Large enterprises with dedicated AI teams who want to replace manual labeling with programmatic weak supervision for text and structured data