If vLLM already solved LLM serving, why did SGLang appear?

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Most builders today are deploying voice interfaces across customer support, virtual assistants, enterprise workflows etc. transforming how organizations engage with their users.
And users? They expect it to just work. Fast responses. Context-aware interactions. Low-brainer handoffs between systems. But behind this kind of simplicity lies a very different reality.
Fragmented systems. Inefficiency. Latency that creeps in unnoticed.
Our solutions architects were challenged with a similar dilemma. Where they were given a Voice AI foundational model training pipeline that was initially split across environments – data processing on one CSP/hyperscaler and model training on Neysa GPUs. This fragmented setup led to increased data movement, higher latency and prolonged training cycles, limiting overall efficiency.
Most builders think the only solution is to choose. We believe otherwise.
Builders today shouldn’t have to compromise on how they would like to build their AI their way. To address the inefficiencies in the existing setup, an integrated architecture was introduced, bringing both data pipelines and GPU-based training into a unified environment on Neysa cloud.
Spin up GPU-powered workloads in minutes. Reduce time-to-result with low-latency access and optimized pipelines that simplify everything from provisioning to inference. No multi-dashboard sprawl, no vendor lock-in.
Enterprise-grade, multi-layered security designed for regulated environments. Role-based access, policy enforcement, real-time audit trails, and zero-trust architecture — built in.
From 1 to 1,000+ GPUs, scale as your models grow. Neysa Velocis is architected to support elastic scaling, hybrid burst, and workload-aware optimization.
Stop burning cycles on idle infra. Transparent billing, spot-aware scheduling, and multi-tiered GPU pricing deliver superior tokens-per-dollar efficiency.
To learn more about the Neysa solutions featured in this story, please contact your Neysa representative