Labellerr: Simplifying AI Data Annotation for High-Performance Models

Labellerr is a powerful data annotation platform designed to streamline the process of labeling image, video, text, and DICOM medical data for machine learning. It combines automated AI-assisted pre-labeling with manual annotation tools to deliver high-quality, ML-ready datasets efficiently. Built for both researchers and enterprises, Labellerr offers a smart feedback loop, active learning, and seamless integration with major ML platforms like GCP Vertex AI, AWS SageMaker, and Azure ML. The platform is trusted across industries including automotive, healthcare, biotechnology, and retail, and is recognized as a G2 2024 Spring High Performer and Easiest To Use in Data Labeling Software.

Key Features:

• Multi-Modal Annotation: Supports image, video, text, and DICOM medical images.
• AI-Assisted Pre-Labeling: Uses smart AI to generate initial labels, accelerating annotation.
• Smart Feedback Loop: Continuously improves labeling accuracy through iterative feedback.
• MLOps Integration: Seamlessly connects with ML training engines for a streamlined workflow.
• Advanced Analytics: Includes annotation analytics dashboards and performance tracking.
• Enterprise-Grade Security: Features AES-256 encryption, TLSv1.2+, and Auth0 authentication.
• Flexible Export: Exports data in ML-ready formats including CSV, JSON, COCO, Pascal VOC, and custom formats.
• Support for Diverse Data Types: Handles jpg, png, wav, mp4, txt, pdf, dicom, lidar, and nifti.
• 24/7 Support & Customer Hosting: Offers round-the-clock support and secure hosting options.

Pricing: Labellerr offers a free Researcher plan, a Pro plan at $499/month, and custom Enterprise pricing. A 14-day free pilot is available with no minimum data commitment.

Conclusion: Labellerr is a highly efficient and user-friendly data annotation solution that empowers teams to build better AI models faster, combining automation, intelligence, and enterprise reliability in one platform.