Powering vision AI
Weaving human and machine intelligence to help deep learning teams reach production at scale
Enriching AI capabilities in the
autonomous driving space
Computer vision is an integral part of driverless vehicles and smart mobility systems, yet most applications in this space are far from being production-ready. This is because model accuracy in autonomous driving can be a matter of life and death, as failed detections could lead to collisions. Furthermore, data varies greatly by location and often requires that many different models work together simultaneously.
To answer such demands, Dataloop’s platform integrates automatic active learning with human-in-the-loop functions for data validation, performed at every step of the automation pipeline. This way, deployed models are continuously fed with new, authentic and validated data that comes directly from your production environment, ensuring that your models produce outputs with only above-threshold accuracy, even in highly dynamic and diverse settings.
Dataloop's real-world mobility applications
Select use cases that Dataloop advances
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Enterprise-grade data engine
Ensuring highest data standards that serve your entire data organization, allowing cross-functional collaboration while keeping your data access internal
“We love working with Dataloop; their data management platform allows us to simultaneously ensure multiple projects are labeled, tasked and QA'd regardless of where our workforce is based.”
“The team at Dataloop provide a powerful platform with a suite of tools. Thanks to Dataloop, we're able to successfully test our algorithms and improve our ADAS and autonomous driving features"
“Data accuracy is critical to the development of our autonomous systems. Dataloop provides our team with a powerful and intuitive platform that allows us to create top quality and accurate datasets”