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Fast distributed SQL query engine for big data analytics.

The data-centric AI platform for high-quality training data and model evaluation.

Kili Technology is a premier Data-Centric AI platform designed to manage the entire lifecycle of training data, moving beyond simple annotation into complex data quality management. By 2026, Kili has solidified its position as the enterprise standard for high-stakes industries like healthcare, defense, and autonomous systems. Its technical architecture centers on a robust GraphQL API and Python SDK, enabling seamless integration into automated MLOps pipelines. The platform excels in 'Model-in-the-Loop' workflows, where pre-annotations and active learning significantly reduce labeling costs while increasing precision. Kili's 2026 iteration features advanced support for RLHF (Reinforcement Learning from Human Feedback), specifically tailored for fine-tuning Large Language Models. It provides a collaborative environment where domain experts, data scientists, and professional annotators can synchronize through rigorous QA workflows, inter-annotator agreement (IAA) metrics, and programmatic labeling. Whether deployed via SaaS, VPC, or on-premise, Kili offers the governance and security features required for SOC2 and GDPR compliance, ensuring that sensitive data assets remain protected while being optimized for high-performance model training.
Kili Technology is a premier Data-Centric AI platform designed to manage the entire lifecycle of training data, moving beyond simple annotation into complex data quality management.
Explore all tools that specialize in annotate image data. This domain focus ensures Kili Technology delivers optimized results for this specific requirement.
Explore all tools that specialize in validate data quality. This domain focus ensures Kili Technology delivers optimized results for this specific requirement.
Explore all tools that specialize in image segmentation. This domain focus ensures Kili Technology delivers optimized results for this specific requirement.
Allows users to write scripts or use heuristics to label thousands of data points automatically based on defined logic.
Dedicated UI for ranking LLM outputs, identifying hallucinations, and fine-tuning alignment.
Multi-stage review processes with blind labeling and consensus metrics.
Seamless integration of pre-trained models to suggest annotations that humans only need to verify.
Specialized viewer for medical imaging including windowing, 3D reconstruction, and multi-planar views.
Identifies which unlabeled data points would be most beneficial for the model to learn from next.
JavaScript-based plugins to customize the annotation interface for highly specific domain tasks.
Sign up for a Kili Technology account via the official website.
Create a new project and select the relevant data modality (CV, NLP, LLM).
Define your ontology—labels, classifications, and relationship attributes.
Import your raw assets using the Kili Python SDK or cloud storage connectors (S3, Azure Blob, GCS).
Configure quality control settings, including consensus and honey-pot tasks.
Set up Model-Assisted Labeling by connecting an external model via API for pre-annotations.
Invite internal teams or external labeling partners to the workspace.
Implement programmatic labeling scripts to automate simple annotation tasks.
Monitor annotator performance and inter-annotator agreement via the analytics dashboard.
Export finalized high-quality labels in your preferred format for model training.
All Set
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Verified feedback from other users.
"Highly praised for its SDK and flexibility, though enterprise pricing is a hurdle for startups."
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