September 23, 2022

SUPA BOLT Platform Walkthrough

SUPA BOLT Platform Walkthrough

SUPA BOLT turns unlabeled data to trusted data with a single, easy-to-use data labeling platform for quality insights.

In this demo video, we walk you through the challenges faced by the data labeling industry today, and how BOLT can help uncover insights to iterate training data. 

 We'll show you the optimum workflow to

  1. Surface and interpret insights
  2. Iterate your instructions
  3. Run and monitor your next batch of data

The speakers are Zi Wei, our Product Manager and Steve, our Head of Business Development.

Start an image annotation project now with $50 credit on us.

Bryce Wilson
Data Engineer at Black.ai

Consistent support

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.

Jonas Olausson
Data Engineer at Black AI
The best interface for self-service labeling.

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.

Sravan Bhagavatula
Director of Computer Vision at Greyscale AI
Launch a revised batch within hours

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.

Sparsh Shankar
Associate ML Engineer at Sprinklr
Really quick

The annotators were really quick. I would upload and 5 minutes later - 10 images done. I checked 5 minutes later - 100 images done.

Puneet Garg
Head of Data Science at Carousell
Good quality judgments

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.

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Let us walk you through the entire data labeling experience, from set up to export

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