Brain Builder

Tailored specifically for deploying Neural Networks and Deep Neural Networks (DNNs) on edge devices, ensuring efficient performance in constrained environments.

Enables the unique implementation of Neurala’s L-DNN, which enhances computational efficiency and processing speed for vision AI tasks.

Facilitates the use of advanced vision AI functionalities, including Detection, Tracking, and Segmentation.

Capable of processing imagery in real-time or near-real-time, significantly reducing latency to less than a tenth of a second in many applications.

Includes comprehensive documentation, example code, and libraries to aid developers in integrating AI capabilities into their applications easily.

Designed to fit seamlessly into existing workflows, allowing developers to leverage AI without extensive overhead.

Works across a range of devices, from single ARM cores to powerful GPU arrays, making it versatile for different deployment scenarios.

Tools for implementing various types of Neural Networks, tailored for edge applications.

Provides functionalities to train and deploy DNNs efficiently in limited computational environments.

Offers a suite of AI algorithms designed for vision applications, simplifying the development process.

Includes a public API to allow developers to easily interact with the SDK and access its features.

Supports both training and inference operations for object classification, tracking, and segmentation.

Engineered to optimize AI processing speed, reducing the time taken for image analysis.

Backed by extensive engineering resources to assist in the integration and development process.

Ensures compatibility with various operating systems and hardware setups, enhancing flexibility for developers.

Provides capabilities for monitoring the performance of deployed models, allowing for efficient troubleshooting.

Access to community forums, tutorials, and resources to facilitate developer learning and collaboration.