Use case
GGUF quantization, batch inference, edge deployment, GPU monitoring, and CPU-optimized serving for production workloads.
Models that work in the lab rarely fit edge devices or tight SLAs without quantization, batching, and serving tweaks. Each step is easy to get wrong.
NEO automates compression, batching, and deployment checks so inference meets latency and memory targets on the hardware you actually run, from laptops to GPUs.
