Kili Technology

Categories: Data Analysis, Coding & Developer Tools, Automation / Agents | Pricing: Freemium | Official Website ↗

Kili Technology provides a robust data annotation platform for building high-quality, trustworthy datasets to train, fine-tune, and evaluate AI/ML models.

Kili Technology offers a comprehensive platform designed for data annotation, curation, and iteration, enabling users to build high-quality datasets for AI/ML models. It supports various data types, including video, image, natural language processing (NLP), large language models (LLMs), optical character recognition (OCR), intelligent document processing (IDP), and geospatial imagery. The platform facilitates collaborative data workflows, allowing teams of varying sizes, from small data science groups to large enterprises with distributed annotators, to manage and scale their annotation processes efficiently. The platform emphasizes enterprise-grade security, offering deployment options on-premise, in the user's cloud, or via Kili's secure infrastructure. It is SOC2 Type II, ISO 27001, and HIPAA certified, making it suitable for sensitive data projects in sectors like defense, healthcare, and government. Kili Technology also provides workforce management services, including sourcing, training, and managing annotators for projects requiring additional support, ensuring the delivery of high-quality labeled data with minimal overhead.

Key Features

Core Labeling Features for various data types (Video, Image, NLP, LLMs, OCR, Geospatial)
Collaboration at scale with defined roles and workflows
Enterprise security and compliance (SOC2 Type II, ISO 27001, HIPAA)
Deployment options: on-premise, in-cloud, or Kili infrastructure
AI-assisted labeling
API & Python SDK support
Workforce management services for additional annotators
Quality review and iteration tools

Pros

Supports a wide range of data types and specialized formats for annotation.
Offers robust security features and compliance certifications for sensitive data.
Facilitates scalable collaboration for teams of various sizes.
Provides AI-assisted labeling to boost productivity.
Offers flexible deployment options including on-premise.
Includes professional services for managed data annotation.

Cons

Pricing for advanced features and larger teams requires custom quotes.
The free plan has significant limitations on asset volume and team seats.
Requires technical understanding for optimal use in AI/ML workflows.
No explicit mention of mobile applications for annotation.
The platform's complexity might have a learning curve for new users.

Use Cases

Building training datasets for AI/ML models
Fine-tuning and evaluating AI models
Annotating images for computer vision tasks
Labeling text for natural language processing (NLP)
Extracting data from documents using OCR and IDP
Evaluating LLM and RAG systems
Managing large-scale data annotation projects

Best For

Data scientists
Machine learning engineers
AI development teams
Enterprises building AI models
Organizations with sensitive data requiring secure annotation

Integrations: Python SDK

Platforms: Web

Watch demo on YouTube ↗

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