Our client is a 20+ year old company in the motion capture space with offices in multiple countries around the globe. They are one of the forerunners in motion capture technology and have worked with the biggest sports brands in the world.
Our client had a challenge to develop motion tracking algorithms for various sports. The team members tasked with data annotation could not handle the workload and the development was lagging behind for want of training data. This resulted in a buildup of backlogs.
The option of hiring more people internally to handle their annotation needs and improve the turn around time would be expensive and time consuming. Our client needed a cost efficient, quality way to scale their training data.
With DataClap’s trained in-house data annotation workforce our client was able to meet their training data requirements.
When we reviewed the guidelines for annotations developed by our client we found some room for improvement. We improved certain aspects of the guidelines that helped streamline the annotation process.
There was a ramp up time of one week to define the process and bring the volume processed upto 2500 images per day which was the target of our client
We have a two tier quality check process that begins with the annotations being checked as the annotation process goes on.
This keeps the feedback loop small and any mistake gets communicated to the whole team instantly and this prevents the mistakes getting repeated.
We develop project specific scripts that help us with the quality check process. We developed scripts that identify manually overlooked mistakes and helped in automating the process and saving much needed time.
Since partnering with us our client has improved the performance of their models significantly. The company has also saved around 30% of staffing costs. Thanks to these, our client can focus its energies and resources on its core competencies.
High growth startups in the artificial intelligence space like our client increasingly prefer specialised managed services and understand its importance in their growth. Even if there are any labels that do not match the level expected by our client, we completely rework on those data without any extra charge.
Our data annotation efforts helped our client implement a smart city project with challenging requirements.
We helped a sports analytics leader in developing AI models for sports analytics.
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Contact us with your requirements and we will set up a team to wok on your free pilot project. No commitments on your side.