Project

AI Sidecar extends local inference beyond GPU memory.

AI Sidecar is a PCIe-attached inference memory accelerator for local LLM workloads. It is designed to keep bulky KV-cache blocks and selected model tensors close to high-capacity memory, while the GPU continues to handle dense transformer compute.

The goal is not to replace the GPU. The goal is to reduce repeated data movement, support larger contexts or more concurrent sessions, and make private AI workloads more practical on controlled infrastructure.

Role

Compute-near-memory sidecar for local model inference

Focus

KV cache, memory movement, quantized storage and routing

Outcome

Larger working sets with measured latency and energy tradeoffs