OneMeta Launches VerbumSDK as Enterprises Shift 56% of AI Workloads to Private Infrastructure

OneMeta Targets Growing Sovereign AI Market with On-Premises SDK

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announced VerbumSDK On-Prem/Edge, extending its real-time translation and transcription capabilities to operate entirely within client-owned infrastructure. The architecture allows organizations to train models on proprietary data and run operations on private servers, air-gapped environments, or edge devices without transmitting information to public cloud providers. This positions OneMeta to capture demand in the sovereign AI market, projected by MarketsandMarkets to expand from $40.0 billion in 2025 to $148.0 billion by 2032—a 20.6% compound annual growth rate1

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. The research identifies on-premises AI infrastructure as the fastest-growing deployment mode within that market.

Enterprise AI Deployment Shift Accelerates

A fundamental change is underway in how enterprises deploy production AI. Broadcom's Private Cloud Outlook 2026, surveying 1,800 senior IT leaders globally, found that enterprises using public cloud as their primary environment for production AI dropped from 56% to 41% in a single year1

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. Meanwhile, 56% now run or plan to run private infrastructure for production AI2

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. This AI deployment shift reflects growing enterprise priorities around data control and compliance, particularly in regulated sectors like healthcare, finance, and government where OneMeta focuses its client base.

VerbumSDK Architecture Enables Full Data Isolation

VerbumSDK's on-premises translation and transcription capabilities address specific enterprise requirements. The system trains custom models using client terminology, records, and language patterns rather than relying on generic models—improving accuracy for industry-specific vocabulary. All conversations, models, and datasets remain on infrastructure the client owns, with nothing transmitted to public cloud providers. The architecture supports fully air-gapped operation on servers with no internet connection, critical for defense and government applications requiring maximum data security. Saul Leal, OneMeta's Founder and CEO, stated: "Our clients and their clients have been asking us to bring our tech stack and CX inside their own walls. We now deploy in the cloud or on-premises, allowing the model itself to be trained on a client's own data and operated entirely within an environment they control"2

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Market Implications for Real-Time AI Applications

The launch reflects broader enterprise concerns about maintaining control over AI deployments while accessing real-time capabilities. Tim Fisher, Senior Vice President of Sales at OneMeta, noted that clients increasingly ask whether they can run the Verbum platform entirely inside their own infrastructure1

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. OneMeta's technology provides translation, transcription, and interpretation across more than 140 languages, targeting organizations with strict data-security and compliance requirements. The SDK architecture maintains the same integration speed on private servers as cloud deployments, eliminating trade-offs between security and implementation velocity. Watch for similar on-premises offerings from other AI vendors as enterprises continue prioritizing deployment models that keep sensitive data within controlled environments.