Thanks to a flexible compiler platform, ML models can be used efficiently on a wide variety of hardware. This solution optimizes the code for the respective architecture and drastically reduces the effort for companies to make their technologies compatible and powerful.

RooflineAI is developing an innovative, retargetable compiler platform that enables edge AI models to be used flexibly on a wide variety of hardware. This platform transforms ML models into machine-readable code that is optimized for the respective target hardware. Companies benefit from a standardized interface that massively reduces the effort required to adapt their technologies. Roofline AI offers a flexible solution that enables the use of models from any framework on different hardware and thus realizes groundbreaking applications. The platform ensures efficient utilization of systems, with up to 4 times less memory consumption and 1.5 times lower latency, without compromising accuracy. Roofline AI also makes model deployment simple and user-friendly. With a single Python call, all necessary steps - from quantization to debugging - can be performed. Developers can rely on effortless implementation, with the SDK providing all the tools for full optimization. Roofline AI accelerates development cycles and maximizes flexibility when selecting new hardware.