ScitiX Launches Enterprise Inference Platform to Centralize AI Operations

The platform operates on a proprietary stack of NVIDIA B200, H200, and H100 hardware, promising 99.9% uptime and a time-to-first-token of roughly one second. By acting as a neutral routing layer, it allows organizations to mix open-source and third-party models without vendor lock-in. Key technical features include intelligent model fallback, session-aware context caching, and zero-retention policies designed to satisfy strict data residency requirements.

Beyond basic execution, ScitiX is prioritizing runtime stability through its SiEval framework. This tool targets the common causes of production failure—such as configuration drift and sandbox timeouts—rather than simply benchmarking model weights. Internal data shows SiEval can achieve up to 10.5x acceleration in evaluation-heavy pipelines, particularly those involving LLM judges and complex code execution. RadixArk, the commercial team behind SGLang, has already integrated the platform into its high-stakes production environments.

The company argues that as agentic workflows proliferate, managing costs and latency via individual point solutions is becoming unsustainable. By centralizing observability and governance, ScitiX seeks to offload the burden of GPU cluster management from enterprise IT teams. The service is available immediately, offering dedicated tenancy options for businesses that require granular control over their AI execution paths.