Kili - 2026 Pricing, Features, Reviews & Alternatives

Kili is a data annotation and labeling platform for building high-quality datasets used to train, fine-tune, and evaluate machine learning models. Designed for data science and AI teams across industries, Kili supports a wide range of annotation types including image, video, text, PDF, and audio, with configurable labeling interfaces and quality review workflows. The platform offers both cloud-based and on-premise deployment options, making it adaptable to organizations with strict data governance requirements.

Kili provides a collaborative environment where data scientists, ML engineers, and annotation teams can manage labeling projects at scale. Built-in consensus and honeypot quality mechanisms help maintain dataset accuracy, while model-assisted pre-labeling reduces manual effort on large annotation tasks. Project management tools, workforce management features, and a Python SDK allow teams to integrate labeling pipelines directly into existing ML workflows.

Enterprises and research organizations use Kili to accelerate dataset production without sacrificing label quality. Support for multi-modal data types, granular role-based access controls, and audit trails make Kili a practical choice for regulated industries and teams handling sensitive data. Analytics dashboards provide visibility into labeler performance, project progress, and quality metrics, giving ML teams the oversight needed to ship reliable training data on schedule.