An AI data infrastructure solution called LayerNext was created especially for computer vision (CV) applications. AI teams can use it to effectively gather, organize, classify, and search massive CV datasets.
Model development and iteration are facilitated by LayerNext’s version control feature, which allows users to arrange and manage their training datasets.The DataLake, a single location for all AI data, is one of LayerNext’s primary features.
This comprises unprocessed photos and videos, carefully chosen data, actual data, and model results. With the integrated viewer offered by DataLake, customers can conveniently search and explore their data while viewing it in one location.Through its Annotation Studio, LayerNext provides additional annotation capabilities that let users tag picture and video data on a large scale.
In order to correct model and label issues, find data gaps, and assess the efficacy of training data, the platform comes with built-in analytical tools.With SDKs and APIs for smooth connection with other computer vision services and apps, the tool places a strong emphasis on teamwork and integration.
Additionally, it offers specialized apps that enable simplified workflows for tasks like annotation and curation.By default, LayerNext is self-hosted, giving users authority over their data and guaranteeing adherence to laws like GDPR and HIPAA.
LayerNext is appropriate for a number of industries, including retail, agriculture, healthcare, and construction, because to its flexibility and security.In general, LayerNext wants to improve the efficiency and cooperation of AI teams by offering automated workflows and data tools specifically designed for computer vision applications.
Teams are able to concentrate on the essential elements of their AI projects by using its intuitive interface and extensive feature set, which streamline the CV workflow.
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