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Labellerr

Labelling made easy-training data to build AI/ML models fast.

Labellerr is a powerful, AI-driven data annotation platform for machine learning, streamlining labeling for images, videos, text, PDFs, and audio. With advanced automation, and seamless cloud integrations, it delivers 99.8% accurate labels, cutting annotation time by up to 80%. Its intuitive interface, robust analytics, and 24/7 support empower AI teams to scale projects efficiently, ensuring high-quality training data for computer vision and NLP models.

A startup from San Francisco, United States that is founded by Puneet Jindal, Sumit Singh.

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Labellerr

Labellerr Reviews and Details

This page is designed to help you find out whether Labellerr is good and if it is the right choice for you.

#AI #Machine Learning #Data Science Tools #Data Science And Machine Learning

Screenshots and images

  • Labellerr
    Image date //
    2025-07-23
  • Labellerr Landing page
    Landing page //
    2021-08-05
  • Labellerr
    Image date //
    2025-07-23

Features & Specs

  1. User-Friendly Interface

    Labellerr features an intuitive and easy-to-navigate interface, making it accessible for users with varying levels of experience in data labeling.

  2. Automated Labeling

    The platform offers automated labeling features, which can significantly speed up the process and reduce the manual effort required.

  3. Scalability

    Labellerr is designed to handle projects of various sizes, making it a flexible solution for both small and large-scale data labeling tasks.

  4. Integration Capabilities

    The platform supports integration with other tools and systems, which helps streamline workflows and improve productivity.

  5. Collaboration Features

    Labellerr includes collaboration tools that enable multiple team members to work on projects simultaneously, enhancing efficiency and coordination.

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Videos

Track Objects 10x Faster in Videos with Labellerr’s SAM 2 Annotation Tool

Annotate Audio 5x Faster with Labellerr’s Tool | Audio Annotation, Transcription, speech Agent

Label 10x Faster: All-in-One Image Annotation Tool for Agriculture, Robotics& Surveillance

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Questions & Answers

As answered by people managing Labellerr.

  1. What makes Labellerr unique?

    Labellerr stands out with its AI-driven automation, achieving 99.8% accurate annotations for images, videos, text, PDFs, and audio, cutting labeling time by 80%. It offers custom workflows, seamless cloud integration (AWS, GCP, Azure), and enterprise-grade security with HIPAA/GDPR compliance.

  2. Why should a person choose Labellerr over its competitors?

    Labellerr outperforms competitors with 99.8% accurate AI-driven annotation, 80% faster workflows, multi-modal support (images, videos, text, PDFs, audio), custom workflows, seamless cloud integration, flexible pricing, and HIPAA/GDPR-compliant security.

  3. How would you describe your primary audience?

    Our primary audience at Labellerr (www.labellerr.com) consists of AI/ML developers, data scientists, and businesses building or refining machine learning models. This includes startups, enterprises, and research teams across industries like computer vision, natural language processing, and audio processing, who require high-quality, scalable data annotation and labeling solutions to train their AI models efficiently.

  4. What's the story behind Labellerr?

    Founded in 2018 by Puneet Jindal, Labellerr tackles the data annotation bottleneck in AI/ML development. Based in San Francisco, it offers a platform with a "Smart Feedback Loop" for automated, high-accuracy data labeling (up to 99.5%) for computer vision, NLP, and audio. Serving industries like healthcare and automotive, Labellerr provides secure, scalable solutions, earning a 4.8/5 G2 rating.

  5. Who are some of the biggest customers of Labellerr?

    Labellerr serves a diverse range of enterprise customers across industries such as automotive, healthcare, retail, and manufacturing. While specific customer names are not publicly disclosed due to confidentiality agreements, Labellerr has secured significant clients, including prominent organizations in medical imaging, autonomous vehicles, and smart city applications.

  6. Which are the primary technologies used for building your product?

    Labellerr uses AI/ML for auto-labeling, a proprietary Smart Feedback Loop for automated data curation, cloud-based infrastructure for scalability, Auth0 with AES-256 and TLSv1.2+ for security, and real-time analytics dashboards with APIs for integration and high-accuracy data annotation.

Is Labellerr good?

External links

We have collected here some useful links to help you find out if Labellerr is good.

  • Public traffic stats of Labellerr

    Check the traffic stats of Labellerr on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.

  • Domain Rating (DR)

    Check the "Domain Rating" of Labellerr on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Labellerr's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.

  • Domain Authority (DA)

    Check the "Domain Authority" of Labellerr on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.

  • Public opinion on Reddit

    The latest comments about Labellerr on Reddit. This can help you find out how popualr the product is and what people think about it.

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Is Labellerr good? This is an informative page that will help you find out. Moreover, you can review and discuss Labellerr here. The primary details have been verified within the last quarter. So they could be considered up to date. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.

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