Connect data seamlessly via S3
or API through your MLOps provider of choice
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Upload locally, via S3 or API through an MLOps provider. If you need help with set up, contact Sales here.
Tasks will be distributed to our trained workforce capable of delivering 100,000+ annotations per day.
Get real-time insights on project progress, analytics and feedback. Run complete QA the next day to measure and verify quality.
You can export annotations at any time to train your model, even while the project is on going.
Receive annotation feedback as we surface label noise – edge cases and rare events – for you.
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Our clients work with Dataloop, Roboflow etc etc. Share the process here?
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If there's one thing that makes SUPA stand out, it's their commitment to providing consistent support throughout the data labeling process. The team actively and efficiently engaged with us to ensure any ambiguity in the dataset was cleared up.
Everything from uploading data to seeing it labeled in real time was really cool. This is just way simpler to use compared to Amazon Sagemaker and LabelBox. I was also very impressed with how the platform delivered exactly what we needed in terms of label quality.
I was also able to view the labels as they were being generated, which gave me quick feedback about the label quality, rather than waiting for the whole batch. This replaced my standard manual QA process using external tools like Voxel's Fiftyone, as the labels were clear and easy to parse through in real-time.
The annotators were really quick. I would upload and 5 minutes later - 10 images done. I checked 5 minutes later - 100 images done.
The team at [SUPA] has been very professional & easy to work with since we started our collaboration in 2019. They've provided us with good quality judgments to train, tune, and validate our Search & Recommendations models.
If there's one thing that makes SUPA stand out, it's their commitment to providing consistent support throughout the data labeling process. The team actively and efficiently engaged with us to ensure any ambiguity in the dataset was cleared up.
Everything from uploading data to seeing it labeled in real time was really cool. This is just way simpler to use compared to Amazon Sagemaker and LabelBox. I was also very impressed with how the platform delivered exactly what we needed in terms of label quality.
I was also able to view the labels as they were being generated, which gave me quick feedback about the label quality, rather than waiting for the whole batch. This replaced my standard manual QA process using external tools like Voxel's Fiftyone, as the labels were clear and easy to parse through in real-time.
The annotators were really quick. I would upload and 5 minutes later - 10 images done. I checked 5 minutes later - 100 images done.
The team at [SUPA] has been very professional & easy to work with since we started our collaboration in 2019. They've provided us with good quality judgments to train, tune, and validate our Search & Recommendations models.
Let us walk you through the entire data labeling experience, from set up to export
Schedule a chat
Our expert annotators will label your data (after undergoing a stringent series of training courses and assessments, of course). They are remote annotators who work part-time on different projects available via our platform. Annotators are assigned to projects automatically once they are qualified for the tasks.
Our expert annotators will label your data (after undergoing a stringent series of training courses and assessments, of course). They are remote annotators who work part-time on different projects available via our platform. Annotators are assigned to projects automatically once they are qualified for the tasks.
Our expert annotators will label your data (after undergoing a stringent series of training courses and assessments, of course). They are remote annotators who work part-time on different projects available via our platform. Annotators are assigned to projects automatically once they are qualified for the tasks.
Our expert annotators will label your data (after undergoing a stringent series of training courses and assessments, of course). They are remote annotators who work part-time on different projects available via our platform. Annotators are assigned to projects automatically once they are qualified for the tasks.
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