Sama Curate

Data Curation

Sama Curate reduces your total cost of ownership (TCO) and development time by providing filtering and curation tools to ensure you only label the data most likely to improve your ML model. We get you into production faster.

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Sama Curate

Sama’s data curation tools help you prioritize labels that will have the greatest impact on your model’s performance.

Sama Curate employs models that interactively and accurately suggest which assets need to be labeled, even on pre-filtered and completely unlabeled datasets.

This smart analysis and curation saves you time and money, quickly optimizing your model accuracy while maximizing your ROI.

What Sama Curate offers

Visualize the diversity of your data

Understand diversity, identify edge cases, and prioritize the most high-value data you can label to improve your models.

Select and curate data

State-of-the-art data curation algorithms provide a continuous feedback loop to optimize the efficiency of your labeling process.

Label your data more efficiently

Get high-quality labels for your models more quickly, and use advanced analytics to detect data drift and proactively update training sets.

Prioritize Labels that Get Your Model into Production

Sama helps you identify the best data to annotate so that you can quickly optimize your model accuracy.

Quicker Turnaround

Smart selection for swifter path to production for your models.

Greater
Data Value

Ensure labels add value, reduce labor costs, and get higher ROI models.

Better Model Performance

Better accuracy and better performing models with less data.

90%

Lower dataset costs by up to 90%

20%

Increase model quality up to 20%

2X

Up to 2X faster product development

Enterprises Rely on Sama Curate

Too much data, too little budget

Pain Point
You’ve collected a lot of data, but you can only afford to professionally annotate some of it. You don’t know how to choose data for annotation, so you’re manually picking what you hope is the right data.

Solution
Curate helps you select the data most likely to improve your model performance overall from your unlabelled data.

No way to leverage your own metadata

Pain Point
You know what you need to annotate, but you have a hard time extracting it from your pool of unlabelled data. You have to manually go through the data to select desired images. You wrote a dataset preprocessing script that’s hard to maintain because it’s not in your model development pipeline.

Solution
Curate provides you with the right filtering tools to find images based on your metadata search criteria. The process can be automated or semi-automated, as needed.

Poor model performance

Pain Point
Your model performs poorly for some object classes so you’re forced to manually find instances of these classes. Worst case scenario: You trigger another data collection initiative to find more desired images, restarting your project and wasting more time.

Solution
Curate offers systematic ways to find images in your datapool that improve your model on desired object classes.

Too much video, too few interesting objects

Pain Point
You have a lot of video footage, but there aren’t many frames which contain interesting objects. You’re stuck sending the entire set of videos for professional annotation, or you assign someone to manually select video sequences for annotation based on intuition.

Solution
Curate can find the video sequences with the richest information so that annotators can focus on the most relevant frames for model training.

Training dataset differs from production data

Pain Point
Your model performs well during its training phase but it has poor performance in production. You find no good tools on the market that speeds up the investigation of your training data vs your production data.

Solution
Curate helps identify key differences between two (or more) datasets. This is important because if your training data isn’t representative of your production data, your model won’t perform well.