'The GPU never reads the same text twice': Belgian startup Corbenic wants to turn your server's SSD into AI memory, but its 14x speedup owes more to reading less

Corbenic AI's Galahad beta saves a model's KV cache to encrypted local NVMe so servers can skip rereading text after GPU memory is cleared or after a restart Founder Sietse Schelpe tells TechRadar Pro no special hardware is needed, but the paper credits most of the 14x speedup to Blaise, a retrieval component, not SSD loading LMCache, Nvidia Dynamo and CMX, WEKA and Phison already persist KV cache to storage; Galahad's edge is exact, fail-closed reuse in one small library Belgian startup Corbenic AI says it can stop GPUs from rereading documents they have already processed, and its founder told TechRadar Pro the trick needs nothing more exotic than the NVMe drive already sitting in the server.

Galahad, which entered beta on October 1 2026 , saves a model's key-value (KV) cache, the attention state built while a model reads a prompt, to encrypted local storage and reloads it the next time the same text appears.

In an email to TechRadar Pro , Corbenic introduced Galahad with the line "the GPU never reads the same text twice," and founder and CEO Sietse Schelpe summed it up as "the SSD a server already has becomes part of the AI's working memory." Catering to a market with plenty of alternatives in tow The timing of Corbenic's announcement is impeccable; with data centers on course to absorb more than 70% of high-end memory chips in 2026 , getting more work out of existing hardware is an easy sell.

But Corbenic's own paper shows its headline 14x speedup owes more to reading less text than to loading saved work, and the company is walking into a field where Nvidia, Phison, and a well-funded open source project already offer something similar.

Galahad's approach is slightly different: In standard serving, a model answering a second question about a document recomputes that document's attention state from the first token, a step called prefill.

Engines such as vLLM and SGLang already reuse that state while it sits in GPU memory, but Corbenic's paper notes it is evicted under memory pressure and lost whenever the process restarts.

Galahad's KV component, Taliesin, writes each block of text's state to disk under a fingerprint of the exact input bytes, the model, and the tenant, then loads it when those bytes reappear.

Schelpe stressed that the stored copy only comes into play once GPU memory has been cleared or the server has restarted.

"So the choice is not SSD or RAM.

It is SSD or computing it all again on the GPU," he told TechRadar Pro, adding that the load "happens once, before the first word of the answer." He volunteered two limits: short texts are not stored because recomputing them is already fast, and network storage is much slower than a local NVMe drive.