Research & Development

Our focus areas.

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Deploy up to 500 devices in 30 mins and reduce the number of learning cycles by 90% and training time x10. Purus in massa tempor nec feugiat nisl pretium.

Lorem ipsum dolor sit amet

Deploy up to 500 devices in 30 mins and reduce the number of learning cycles by 90% and training time x10. Purus in massa tempor nec feugiat nisl pretium.

Lorem ipsum dolor sit amet

Deploy up to 500 devices in 30 mins and reduce the number of learning cycles by 90% and training time x10. Purus in massa tempor nec feugiat nisl pretium.

Lorem ipsum dolor sit amet

Deploy up to 500 devices in 30 mins and reduce the number of learning cycles by 90% and training time x10. Purus in massa tempor nec feugiat nisl pretium.

Their Data engineers are very experienced in working with timeseries data and implemented several key new parts of the Machine Learning Pipeline. I can only suggest anybody concerned with time-series data to approach T-DAB

Sanchit nardekar
Element Six

Continuous learning.

Enabling the creation of scalable networks and continuously & collaboratively learning devices.

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Project name

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Project name

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Research partnerships

Only model parameters are shared from edge devices on the network, which are aggregated and encrypted. This ensures data confidentiality and avoids any risk involved with the transfer or large volumes of sensitive data.

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