Introduction
Visual Layer is an AI-powered platform that transforms how data professionals organize, explore, and enrich vast collections of unstructured video and image data. By leveraging advanced automation, it accelerates manual data curation by 100x, ensuring the creation of high-quality visual datasets for AI training. This streamlined process not only improves model accuracy and performance but also delivers actionable, data-driven insights at scale, empowering professionals to make faster, more informed decisions with precision and efficiency.
Our Work
Our team developed an intuitive user interface for Visual Layer, transforming the way image and video datasets are managed at scale. With advanced searching, filtering, and segmentation capabilities, the platform enables efficient browsing and organization of datasets based on text, specific objects identified within images, and metadata.
Offering a multifaceted array of features, including automated data labeling, enhanced object identification, contextual metadata enrichment, and refining image annotations, data professionals can efficiently explore , curate, organize, and enrich datasets, all while enhancing data quality and reducing operational costs.
Outcome
Empowering data technicians, our team’s contribution has optimized the management of large-scale image and video datasets. With cutting-edge features like object recognition, and metadata filtering, datasets can be quickly accessed and organized, improving operational efficiency. By integrating automated tagging, precise image classification, and metadata enhancement, we’ve streamlined workflows, delivering more accurate insights.