Optimizing Machine Learning Inference at Scale

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.

Learn More


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 More


Recommendation 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.

Learn More

Trusted By