TuringData Cache Fabric is a software-defined inference memory layer that orchestrates KV cache across GPU memory, host memory, local NVMe, and optional TuringData shared storage. It integrates with leading inference engines through standardized APIs and manages cached context across available memory and storage tiers.

By persisting reusable prefixes and offloading KV data beyond scarce GPU memory, Cache Fabric reduces repeated prefill computation, lowers time to first token, and supports larger batch sizes and greater concurrency. Organizations can make better use of existing GPU, CPU, and storage resources while scaling long-context and agentic inference without continually adding GPUs or HBM.