These are the questions we hear most often from engineering and product teams evaluating Neurala as a technology partner.
QWe already have an AI stack. Does L-DNN replace it or work alongside it?
L-DNN is designed to integrate, not replace. It works as a library within your existing software architecture, living alongside your current inference pipeline, camera SDK, or platform software. The integration scope is defined during the discovery phase, where we assess how L-DNN fits alongside what you already have.
QHow long does a typical integration take?
It depends on the complexity of your environment and the scope of the integration. Discovery and scoping typically takes days to a few weeks. The engineering and integration phase varies from weeks to several months depending on hardware complexity, custom optimization requirements, and how tightly coupled the integration needs to be with your existing system. We move as fast as your team can move with us.
QDo end users need AI or machine vision expertise to use it?
No, and that’s a core design goal of L-DNN. The technology is specifically built so that end users without AI backgrounds can train accurate vision AI models from a handful of images, in minutes. FLIR and Sony both chose Neurala specifically because of this - their customers needed to use AI without becoming AI experts.
QWhat happens to image data?
It stays on the device. The full L-DNN workflow - including training - runs locally. Image data is never transmitted to a cloud server, never stored externally, and never touches Neurala’s infrastructure. This is an architectural characteristic, not a configuration option, which means it remains true regardless of network conditions or connectivity.
QWe’re evaluating other AI platforms too. What makes Neurala different?
Most AI platforms are built for data scientists developing models in the cloud. They require large datasets, GPU infrastructure for training, and significant AI expertise to operate. L-DNN was built for embedding into real products - edge training with minimal data on standard hardware and without cloud dependency. If your evaluation criteria include hardware footprint, data privacy, or end-user accessibility, those are areas where L-DNN offers meaningful differentiation, not just different positioning.
QIs there a pilot or evaluation before a full engagement?
The first step is a direct technical conversation with our engineers - no commitment, no sales process. We respond quickly, and we’ll tell you honestly within that conversation whether L-DNN is a good fit for your use case. If it is, we'll work together to determine the most appropriate first step, whether that's a scoped evaluation, a proof of concept, or a full integration.