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Kili SIMPLE is our workforce solution for machine learning teams facing large scale data annotation challenges.

No need to exert effort on data labelers, we'll handle it for you. Our global network is equipped with the best platform and expertise to tackle even the most complicated labeling needs.

Whether that's text, documents, image, video, or satellite imagery - we'll make it SIMPLE.


"It was an end-to-end solution for us... We got high-quality experts as external labelers..."

ViktorChief Data Officer at an Auto Insurance Company

"The labelers that Kili provided to support our project are very good. Also, Kili’s support team made sure to train them on the platform. This accelerated considerably our progress and improved the quality of the annotations."

Marie de Leseleuc
Marie de LeseleucData Science and Analytics Director at Eidos-Montréal

Kili's qualified labelers helped us tackle complex labeling on CT and X-Ray scans - making it easier for us to scale our efforts.

MarcelProject Lead at a Pharmaceutical Company

How it works

Upload your data sample
Let us know the expected volume of your annotation project. Share a sample of your dataset for annotation and provide specific labeling guidelines for the annotation tasks.
Receive the quote & kickstart your project
Receive a transparent quote promptly, and we'll get started on annotating your project immediately.
Monitor your project's progress on Kili
Get real-time tracking and visibility into the progress of dataset labeling with our advanced quality features. You stay in control of the precision and quality of your data.
Get your full batch labeled
Receive your fully labeled dataset on time and with a 95% accuracy guarantee. Not satisfied with the quality? Unhappy with the results? We reannotate at no extra cost.

Accelerate your AI projects

Any use case, Any taskAny use case, Any taskImage, video, satellite, text, document, conversational. From bounding boxes to segmentation, from OCR to relations you are covered.
Quality GuaranteeQuality GuaranteeWe guarantee a 95% quality standard based on the validated requirements established with the calibration batch.
Start fastStart fastReceive a quote and initiate your outsourced data labeling within 2 business days.

Real-time visibilityReal-time visibilityKili's unique review interface and analytics provide valuable real-time insights into project progress and quality.
Built-in feedback loopBuilt-in feedback loopKili's collaboration tools and quality checks help identify errors and improve labeler performance.
Transparent priceTransparent priceNo surprises. No hidden fees. You will receive a clear price at the end of the calibration batch. Projects start at just $7 per hour.

They trust us

Frequently Asked Questions

What types of data can Kili Simple process?

Kili Simple handles various data types, including images, videos, texts, and documents, catering to various AI project needs.

What makes Kili Simple different from other data labeling services?

Kili Simple has the benefit of partnering with a powerful state-of-the-art data labeling tool with a well-trained professional workforce with a wide array of domain-specific knowledge and languages.

We have experience working with enterprises with large volumes of data requiring high-accuracy labeling.

Why should I hire a professional workforce?

Hiring a professional workforce can help speed up and scale your data labeling projects. Skilled labeling workforces boast extensive training in data labeling across diverse domains and use cases. A professional data labeling workforce allows businesses to adapt labeling workflows to project requirements. Check out our article here to learn more about hiring professional workforces.

What are the best practices for submitting our data labeling guidelines?

Communicating clear data labeling guidelines is essential for getting your data labeled accurately, whether by our team or others. Some tips would be to set a gold standard for labelers to follow, as well as advice on how to handle more ambiguous and edge cases. Check out our example of a data labeling guide, here.


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