LayerNext: Streamlining Computer Vision Data Management

LayerNext is an AI data infrastructure tool purpose-built for computer vision (CV) projects. It simplifies the entire data lifecycle, from collection and curation to labeling, searching, and analysis, empowering AI teams to build and iterate on models more efficiently.

Features

• DataLake: A unified repository for all your AI data – raw images and videos, curated data, ground truth, and model outcomes. Includes a built-in viewer for easy visualization and search.
• Annotation Studio: Provides powerful annotation tools for labeling image and video data at scale.
• Built-in Analytics: Offers analytic tools to assess training data effectiveness, identify data gaps, and pinpoint model and label errors.
• Collaboration & Integration: Features SDKs and APIs for seamless integration with other CV applications and services, along with specialized apps for streamlined workflows.
• Self-Hosted & Secure: Provides users with complete control over their data, ensuring compliance with regulations like HIPAA and GDPR.

Benefits

• Enhanced Productivity: Automate workflows and simplify the CV process, allowing teams to focus on core AI development.
• Improved Collaboration: Facilitate seamless teamwork through integrated tools and collaborative features.
• Data Security & Control: Maintain complete control over your data with a self-hosted solution and robust security measures.
• Scalability & Flexibility: Handle large-scale datasets and adapt to evolving project needs.

Use Cases

LayerNext is suitable for diverse industries including:

• Retail: Analyzing customer behavior through image and video data.
• Agriculture: Monitoring crop health and yield using drone imagery.
• Healthcare: Improving diagnostics and treatment planning through medical image analysis.
• Construction: Enhancing site safety and project management with visual data.

LayerNext ultimately empowers AI teams to unlock the full potential of their computer vision projects through efficient data management and streamlined workflows.