Explore & filter focus review on data that matter
Filter on data slices with low quality metrics.
Focus human review on it to have the most impact in your pipeline.
[1]
Find and fix issues in ML datasets
Supervise quality level & improvements to ensure low-errors datasets. Simplify advanced collaboration workflows. Leverage programmatic QA. Explore datasets and identify the data that matters to improve the model’s performance.
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[2]
Advanced quality metrics to get insights
Look at the consensus by class to know when your ontology needs to be reshuffled. Look at the labelers’ disagreement to identify misunderstandings among your annotator population. Look at the class imbalance to ensure you build a balanced dataset. And much more.
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[3]
Issues to spot anomalies, workflows to solve errors
Create a communication flow between annotators and reviewers. Let reviewers create and track issues at the finest object level. Notify the labelers. Resolve once fixed.
Talk to an expertThey trust us on their data-centric journey
"Kili's customer support is best in-class. We solve issues much faster and it has a direct impact on our performance."
"Great companies like Kili Technology, [...] have already adopted this data-centric AI approach."
"Kili is bringing added value in the management of our projects and this is quality."
"Kili enables us to improve our models’ performance and scale our AI projects as fast as our business needs."
"We are very satisfied with our collaboration with Kili. We saw a performance improvement of our model of 3.5%"
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Discover how Kili is helping companies in different sectors build responsible, effective AI on a foundation of good data.
