LayerNext is a special tool for computer vision projects. It helps AI teams efficiently handle large-scale datasets by collecting, organizing, and labeling them. With features like version control, users can easily manage training datasets, making model development smoother.
The DataLake feature acts as a central hub for all AI data, including images, videos, curated data, and model outcomes. It has a viewer for easy data visualization and searching. LayerNext also provides Annotation Studio for labeling data at scale and built-in analytics to assess training data effectiveness.
Layernext Features
- Cloud integration: You can integrate Layernext with your S3, GCP, or Azure cloud storage buckets and access your data from anywhere.
- Data exploration and organization: You can search and explore raw images and videos, curated data, metadata, ground truth and model outcomes in a single, easy-to-navigate data lake with a built-in viewer.
- AI advanced features: You can leverage Layernext’s advanced AI features to enhance and streamline your workflows. These features include auto-tagging, embedding generation, and auto-annotation for your images and videos.
- Customization and security: You can easily customize Layernext to align with your unique workflow and seamlessly integrate with any other AI tools.
- API and SDK integration: You can integrate Layernext with your existing tools and frameworks using its API and SDK.
FAQs About Layernext
What is Layernext?
Layernext is a no code platform to create custom AI agents to automate routine tasks, get answers from your data and generate business insights.
How does Layernext work?
Layernext uses the best Large Language Models (LLMs) and Retrieval Automated Generation (RAG) to produce accurate answers for questions and solve complex tasks.
How can I get started with Layernext?
You can book a demo or sign up for a free trial on their website. You can also read their documentation to learn more about the core concepts, UI, data integration, and API of Layernext
