KAYTUS Upgrades AI Platform for On-Premises Use

SINGAPORE, Sept. 21, 2026 /CourierPR/ -- KAYTUS, a leading provider of AI infrastructure solutions, today announced a major upgrade to its enterprise AI platform, MotusAI. The release empowers enterprises to custom-build, govern, and scale on-premises "Token Factories," deploy AI agents into production, and keep sensitive data within their own infrastructure, all while reducing annual token-related operating costs by 30%, 50%.

As enterprise AI advances from simple LLM queries to autonomous multi-agent systems, tokens are becoming the computing currency powering core business workflows. Deploying agentic AI across the enterprise at scale brings three critical infrastructure challenges into focus: security and compliance risks, latency and service reliability, and uncontrolled token costs.

The Challenge: Scaling AI Agents While Maintaining Control

As enterprise AI advances from simple LLM queries to autonomous multi-agent systems, tokens are becoming the computing currency powering core business workflows. Deploying agentic AI across the enterprise at scale brings three critical infrastructure challenges into focus: security and compliance risks, latency and service reliability, and uncontrolled token costs.

Security and Compliance Risks: Sending proprietary source code, customer records, and core business logic through public clouds or LLM APIs can expose sensitive data and create regulatory compliance risks. For example, a Japanese cloud provider runs its core platform on MotusAI, offering shared GPU resources and end-to-end training and inference workflows to more than 30 enterprise clients. This allows the firm to retain control over sensitive data and compliance policies.

Latency and Service Reliability: Multi-step agent reasoning and tool orchestration can trigger unpredictable traffic spikes. Without elastic scheduling, compute resource bottlenecks can delay Time to First Token (TTFT) and cause failed requests, compromising service-level agreements and user experience. For instance, a financial services firm replaced its existing platform with MotusAI across eight GPU servers, enabling metered token services with centralized governance for internal risk analysis and security compliance.

Uncontrolled Token Costs: Unmonitored model usage and missing departmental quotas can drive escalating API costs, leaving enterprises without clear spending accountability across business units. A financial services firm, for example, replaced its existing platform with MotusAI across eight GPU servers, enabling metered token services with centralized governance for internal risk analysis and security compliance.

MotusAI: A Solid Foundation for End-to-End Token Lifecycle Management

MotusAI addresses these challenges with a secure, on-premises foundation unifying token production, distribution, and operations. Enterprises in financial services, healthcare, and government can scale AI while retaining control over sensitive data and compliance policies. MotusAI keeps inference processing, model weights, and context within the enterprise security perimeter.

Reliable Service Quality: MotusAI transforms on-premises GPU clusters into a resilient token production engine, sustaining sub-second responsiveness even during peak demand. For example, a Japanese cloud provider runs its core platform on MotusAI, offering shared GPU resources and end-to-end training and inference workflows to more than 30 enterprise clients. This allows the firm to retain control over sensitive data and compliance policies.

MotusAI's enterprise-grade API gateway streamlines model deployment and access for internal development teams. For instance, a Japanese cloud provider runs its core platform on MotusAI, offering shared GPU resources and end-to-end training and inference workflows to more than 30 enterprise clients. This allows the firm to retain control over sensitive data and compliance policies.

Precise Governance and Lower Cost: MotusAI delivers end-to-end operational visibility to eliminate waste compute resources. For example, a Japanese cloud provider runs its core platform on MotusAI, offering shared GPU resources and end-to-end training and inference workflows to more than 30 enterprise clients. This allows the firm to retain control over sensitive data and compliance policies.

Advancing the Future of Enterprise AI at Scale

With MotusAI, KAYTUS brings secure, high-throughput production on premises, helping enterprises protect sensitive data, operate independently of cloud APIs, and further increase the GPU utilization. The upgraded MotusA platform enables organizations worldwide to deploy and scale agentic AI securely and efficiently.

KAYTUS is a leading provider in AI infrastructure and liquid cooling solutions, delivering a diverse range of innovative, open, and eco-friendly products for cloud, AI, edge computing, and other emerging applications. With a customer-centric approach, KAYTUS is agile and responsive to user needs through its adaptable business model. Discover more at KAYTUS.com and follow us on LinkedIn and X.