Gate News message, April 15 — Synapse Software has integrated TurboQuant, a vector quantization algorithm developed by Google Research, into its Synap OCR IX solution to enhance document AI capabilities while reducing enterprise AI adoption costs.
TurboQuant compresses KV cache used by large language models (LLMs) and vision language models (VLMs), reducing memory consumption when processing long documents. This enables faster data processing on the same GPU infrastructure. The technology addresses memory bottlenecks that previously required expensive GPU infrastructure, particularly for handling extended contexts and large-batch processing without performance degradation.
Synapse Software also supports CPU-based environments for enterprises unable to deploy GPU infrastructure. Through precision profiling, the company achieved CPU-only inference processing of approximately 100 documents per minute with quality loss kept below 1%, lowering total cost of ownership (TCO). The flexible infrastructure approach enables AI OCR adoption in security-sensitive sectors such as finance and public administration, where on-premises deployment and infrastructure constraints have previously hindered AI implementation.
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