KAYTUS Unveils Upgraded MotusAI to Revolutionize Large AI Model Deployment
KAYTUS, a leader in end-to-end AI and liquid cooling solutions, has announced the release of the latest version of its MotusAI AI DevOps Platform at ISC High Performance 2025. This upgraded platform delivers significant advancements in large model inference performance, tool compatibility, resource scheduling, and system stability, designed to accelerate the deployment of large AI models. With these enhancements, KAYTUS aims to streamline AI adoption and drive innovation across key industries such as education, finance, energy, automotive, and manufacturing.
As large AI models become increasingly integrated into real-world applications, enterprises are leveraging their capabilities to generate tangible value across diverse sectors. However, many organizations face persistent challenges in AI adoption, including prolonged deployment cycles, fragmented open-source tool management, low compute resource utilization, and stringent stability requirements. To address these pain points, KAYTUS has engineered the latest version of MotusAI, purpose-built to simplify AI deployment, enhance system stability, and optimize infrastructure efficiency for large-scale operations.
Boosting Inference Performance for Seamless AI Deployment
Deploying AI inference services is a complex process that involves service deployment, management, and continuous health monitoring. Achieving high performance and stability requires significant investments in time, manpower, and technical expertise. The upgraded MotusAI addresses these challenges by delivering robust large-model deployment capabilities that align visibility and performance seamlessly.
By integrating optimized frameworks such as SGLang and vLLM, MotusAI ensures high-performance distributed inference services that can be deployed quickly and with confidence. Designed to support large-parameter models, MotusAI leverages intelligent resource and network affinity scheduling to accelerate time-to-launch while maximizing hardware utilization. Its built-in monitoring capabilities span the entire stack—from hardware and platforms to pods and services—offering automated fault diagnosis and rapid service recovery. Additionally, MotusAI supports dynamic scaling of inference workloads based on real-time usage and resource monitoring, ensuring enhanced service stability and reliability.
Comprehensive Tool Support to Accelerate AI Adoption
The rapid evolution of AI technologies has led to a growing ecosystem of development tools, making it challenging for developers to efficiently select, deploy, and manage these resources. To address this complexity, the upgraded MotusAI provides extensive support for a wide range of leading open-source tools, enabling enterprise users to configure and manage their model development environments on demand.
Built-in tools such as LabelStudio accelerate data annotation and synchronization across diverse categories, improving data processing efficiency and expediting model development cycles. MotusAI also offers an integrated toolchain for the entire AI model lifecycle, including:
- LabelStudio and OpenRefine for data annotation and governance.
- LLaMA-Factory for fine-tuning large models.
- Dify and Confluence for large model application development.
- Stable Diffusion for text-to-image generation.
These tools empower users to adopt large models quickly and boost development productivity at scale, reducing the barriers to entry for organizations looking to harness the power of AI.
Hybrid Training-Inference Scheduling for Maximum Resource Efficiency
Efficient utilization of computing resources remains a critical priority, especially for AI startups and small to mid-sized enterprises in the early stages of AI adoption. Traditional AI clusters typically allocate compute nodes separately for training and inference tasks, limiting flexibility and efficiency in resource scheduling.
The upgraded MotusAI overcomes these limitations by enabling hybrid scheduling of training and inference workloads on a single node, allowing for seamless integration and dynamic orchestration of diverse task types. Equipped with advanced GPU scheduling capabilities, MotusAI supports on-demand resource allocation, empowering users to efficiently manage GPU resources based on workload requirements. It also features multi-dimensional GPU scheduling, including fine-grained partitioning and support for Multi-Instance GPU (MIG), addressing a wide range of use cases across model development, debugging, and inference.
MotusAI’s enhanced scheduler significantly outperforms community-based versions, delivering a 5× improvement in task throughput and a 5× reduction in latency for large-scale POD deployments. It enables rapid startup and environment readiness for hundreds of PODs while supporting dynamic workload scaling and tidal scheduling for both training and inference. These capabilities ensure seamless task orchestration across a wide range of real-world AI scenarios.
Driving AI Innovation Across Industries
The upgraded MotusAI platform is set to play a pivotal role in accelerating AI adoption and fueling business innovation. By addressing critical challenges such as prolonged deployment cycles, fragmented tool management, and inefficient resource utilization, MotusAI empowers organizations to overcome barriers to large AI model deployment. Its streamlined workflows, comprehensive tool support, and advanced scheduling capabilities make it an ideal solution for enterprises seeking to unlock the full potential of AI.
“With the latest version of MotusAI, we’ve taken a significant step forward in simplifying and accelerating AI deployment,” said a spokesperson for KAYTUS. “Our goal is to provide enterprises with the tools they need to innovate faster, operate more efficiently, and stay competitive in an increasingly AI-driven world.”
About KAYTUS
KAYTUS is a leading provider of end-to-end AI 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.
