As organizations move AI applications into production, infrastructure becomes more complex, and the need for different AI models can mean working with separate providers, computing environments, and technical integrations. Organizations that need to follow stricter data residency or security requirements may find that the only way to meet those frameworks is by building and managing their own infrastructure.
Bunyan Inference Hub brings these elements together in one platform. Hosted in Saudi Arabia, it enables organizations to keep their data and AI workloads within the Kingdom, access a catalogue of AI models or bring their own, and use computing resources without managing separate infrastructure for each model or use case. Customers access predefined token bundles across supported models and workloads, with dedicated GPU infrastructure available for organizations that need additional capacity or isolation.
This is enabled by OmniOps’ proprietary inference optimization engine, developed by the company’s R&D team. The engine adapts how AI models run on available hardware to match workload requirements, helping organizations improve GPU utilization, reduce the cost per token, and maintain consistent performance as demand grows, without having to manage the underlying infrastructure.
The platform can run across different GPUs and AI accelerators rather than relying on a single hardware provider. It routes requests to the appropriate model and computing resources, manages infrastructure scaling, and monitors performance and usage. Customers can also set usage limits and track token consumption across teams.
“As entities embrace AI across functions and applications in their operations, ensuring that the consumption of AI models is managed efficiently and with the correct security and cost guardrails has never been more critical,” commented Mohammed Altassan, Founding CEO of OmniOps. “The new hub brings together our proprietary Bunyan Inference technology and experience in sovereign AI deployment in a simplified platform that public and private sector organizations can plug into their operations and use to deploy AI solutions more efficiently.”
The launch comes as demand for AI inference infrastructure grows globally, with more organizations moving AI models into production. Research by ServiceNow shows that Saudi-based entities have increased spending on AI by 124% year-on-year and plan to dedicate 20% of their IT budgets until 2027 to artificial intelligence solutions across their organization. Meanwhile, Gartner forecasts that global spending on AI inference workloads will reach $23.3 billion by the end of 2026.
