Case Study: Raptor Maps reduces time-to-model by 83% with V7 Darwin

Raptor Maps reduces time-to-model by 83% with V7

Raptor Maps, a provider of an integrated operating system for the solar industry, faced significant bottlenecks in its machine learning development. Their outdated in-house data annotation tool extended their time-to-model to nearly a year, hindering their ability to deliver solutions to customers quickly. To advance their research in autonomous solar mapping and continuous robotics, they needed a modern training data platform to manage large datasets and complex human-in-the-loop processes, leading them to partner with V7 and use its Darwin platform.

By implementing V7, Raptor Maps drastically streamlined its annotation and project management workflows. The use of V7's auto-annotation, model-in-the-loop features, and external labeling workforce reduced their average time-to-model from 12 months to just 4-8 weeks, an 83% reduction. This acceleration from V7 allows Raptor Maps to deliver prototypes to customers faster, test more solutions, and advance the use of robotics in the renewable energy sector, all while reducing operational costs.

Raptor Maps