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Kili Technology

Data labeling platform for creating high-quality datasets to train AI models.

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What is Kili Technology?

Kili Technology is a data labelling platform designed to help organisations create high-quality training datasets for AI models. The platform accelerates the annotation process, enabling teams to build datasets significantly faster than manual labelling by combining automated tools with expert human annotation. It supports all types of unstructured data including images, text, video, and audio, making it flexible for various AI projects. The platform offers programmatic quality assurance to identify and correct labelling errors automatically, combined with access to professional labellers who maintain 95% quality standards. This dual approach ensures datasets meet strict accuracy requirements whilst reducing the time spent on manual review. The workflow is designed to simplify data operations, from initial annotation through final quality checks. Kili Technology is suited for enterprises in healthcare, finance, technology, and other sectors where high-quality training data directly impacts AI model performance. Organisations with large-scale data labelling needs benefit most from the platform's ability to handle diverse data types and volume at pace.

Key features

Automated annotation

AI-powered tools speed up labelling of large datasets

Multi-format data support

Handles images, text, video, audio, and other unstructured data

Programmatic quality assurance

Automated tools identify and flag labelling errors

Expert labelling services

Access to professional annotators with quality guarantees

Workflow management

Organises annotation, review, and approval processes

Pros & cons

Advantages

  • Significantly reduces time to create training datasets
  • High accuracy through expert workforce and automated quality checks
  • Flexible data format support for diverse AI projects
  • Scales from small projects to enterprise-scale operations
  • 95% quality assurance standard from professional labellers

Limitations

  • Requires clear labelling guidelines to work effectively
  • Costs scale with data volume, which can be significant for large projects
  • Setup and configuration require time to establish labelling schemas
  • Quality depends on how well initial requirements are defined

Use cases

Creating large image datasets for computer vision model training

Annotating text data for natural language processing models

Labelling video frames for video analysis and object detection

Medical image annotation for healthcare AI applications

Product data classification for e-commerce and search models

Ready to try Kili Technology?

Pricing

Starter

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Entry-level plan for small projects; includes automated annotation tools and basic quality assurance

Professional

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Mid-scale projects; expert labelling services, programmatic QA, multi-format support

Enterprise

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Large-scale operations; unlimited data volume, dedicated support, custom workflows, SLA guarantees

Get started with Kili Technology

Click through to Kili Technology and start using it now.