We optimize real-time machine learning inference workloads for multiple applications in cloud or enterprise data centers and in edge applications. Our products, expertise and IP ensure all available compute resources are optimized to achieve the lowest deterministic latency and superior throughput, cost and energy.
For financial companies wishing to use ML to make automated trading-related decisions faster than their competitors, VOLLO provides that competitive advantage. Audited performance results for the STAC Research ML inference benchmark confirm that VOLLO has the lowest latency as well as high throughput density and energy-efficiency.
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For large scale deployments of ASR, CAIMAN-ASR enables cost savings of up to 90% compared with GPUs.
For natural end-to-end conversational AI, latency becomes critical. CAIMAN-ASR delivers speech transcription at extremely low and deterministic latency compared with traditional approaches.
Learn MoreRecommendation models power the recommendation systems behind search, adverts & personalized content. Performance of these models is often constrained by system memory. We can eliminate this constraint, increasing compute density by up to 10x on existing infrastructure.
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Developers of wireless telecoms infrastructure, wishing to use ML to improve service quality and reduce costs can benefit from the extremely low latency inference and model flexibility that VOLLO can deliver. Audited performance results for the STAC Research ML inference benchmark confirm that VOLLO has the lowest latency as well as high throughput density and energy-efficiency.
Learn MoreThe extremely low latency that VOLLO achieves for neural network models and decision trees delivers a significant benefit in cyber security, industrial safety, electronic warfare and many other latency-critical applications. Audited performance results for the STAC Research ML inference benchmark confirm that VOLLO has the lowest latency as well as high throughput density and energy-efficiency.
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