Kili Technology
KILI TECHNOLOGY
Kili Technology
KILI TECHNOLOGY
Kili Technology
KILI TECHNOLOGY
Labeling Platform for High-Quality AI Training Data
Kili Technology is a comprehensive labeling tool where you can label your training data fast, find and fix issues in your dataset, and simplify your labeling operations. Kili Technology dramatically accelerates the building of reliable AI.
To create training datasets fast with Kili Technology, you are able to leverage:
- Customizable interfaces for all your data: Kili Technology natively supports image, video, text, PDF documents, satellite imagery, and conversations. Leverage advanced UX that speeds up labeling and prevents tagging errors. Customize interfaces and validation rules based on your use case, and labeling process.
- Powerful workflows for fast & accurate annotation: Control your labeling queue to prioritize assets, assign assets to specific labelers or add validation rules. Set a review pipeline to spot inconsistencies and send assets back to the labelers.
- Automation tools to speed-up labeling: Apply interactive segmentation and tracking to accelerate labeling without compromising quality. Leverage your own-model predictions to pre-label. Use active learning to focus on human labeling and review where it will have the most impact.
To find & fix the issues in your ML dataset, you can:
- Focus review on data that matters: Create a communication flow between annotators and reviewers. Iterate quickly with annotators on labels to modify. Provide continuous feedback to your labeling team to avoid drift in quality.
- Quantify quality with insights from advanced quality metrics: Look at the consensus by class to know when your ontology needs to be reshuffled. Look at labelers’ disagreements to identify misunderstandings among your annotator population. Filter on data slices with low-quality metrics. Compare quality between labelers or against an industry standard.
- Increase data quality with programmatic error spotting: Programmatically spot errors by building automated QA scripts in the labeling interface. Use error detection models to automatically find and fix issues in your ML datasets.
- Orchestrate all your quality strategies with automated workflows: Fully automate & build custom workflows to scale your labeling operations.
To simplify your labeling ops, Kili Technology allows you to:
- Import & export data effortlessly: Integrate directly Amazon, Google, and Microsoft cloud storage to automatically start labeling without having to move your data. Track all the intermediary changes in your data and export versioned data directly in the format of your model (YOLO, PASCAL VOC, etc).
- Manage your team at scale: Easily assign predefined roles (admin, manager, reviewer, labeler) to control users’ responsibilities in projects. Authenticate with specific identity providers for maximum convenience and security. Ensure the highest level of data governance & security.
- Automate your MLOps infrastructure: Use webhooks to take specific actions like starting a model training, performing active learning to generate pre-labels or versioning. Create a feedback loop between your model experiments and newly produced labels. Leverage Kili API and Python SDK to connect any ML stack.
At Kili Technology, we believe that focusing on high-quality training data, that is consistently labeled, is the way to unlock the value of AI. Today, we continue our journey to empower all businesses to transform unstructured data into high-quality data to dramatically accelerate the build of reliable AI.
To discover more advanced plans, check our pricing plans and talk to our team at https://kili-technology.com/pricing