SmartX officially announced the release of the SMTX AI Platform Enterprise Edition. By optimizing heterogeneous computing power management, high availability for inference services, and multi-tenant governance, the platform enables unified management of computing resources and models. It is designed to meet the diverse demands of MaaS (Model-as-a-Service) in production environments through unified model resource delivery.
Simple, Flexible, and Open: Addressing New Trends in AI Infrastructure O&M
As AI Agents transition from Proof of Concept (PoC) to large-scale implementation, the underlying MaaS infrastructure faces stricter requirements. It must not only rapidly deploy and manage models of different locations, types, and specifications but also support flexible scheduling and efficient utilization of limited computing resources. The SMTX AI Platform addresses these challenges with a focus on model management, defined by three core advantages:
- Simple: Eschewing bloated features in favor of “purpose-built” functionality for the entire model lifecycle. An intuitive visual interface ensures model deployment and O&M are ready out-of-the-box.
- Flexible: Infrastructure-agnostic design. It can be deployed independently or seamlessly integrated with the SmartX Enterprise Cloud Platform to adapt to diverse deployment scenarios.
- Open: Broadly compatible with mainstream community models and inference engines. It supports a wide range of global and domestic AI chips, preventing vendor lock-in.
Core Highlights: Solving Four Major Challenges in Model Deployment
To tackle common engineering hurdles in enterprise AI adoption, SMTX AI Platform provides targeted technical innovations:
- Optimizing Initial Investment and Resource Utilization. Enterprises often struggle with “computing silos” and the inability to reuse existing hardware. The platform supports unified management of heterogeneous GPUs (including Nvidia, Intel, AMD, and Ascend), significantly boosting utilization and allowing businesses to validate AI value quickly using existing resources.
- Simplifying Model File Management. Fragmented storage and multiple versions often lead to redundancy and chaos. The platform features a built-in unified model repository, streamlining management and distribution while drastically reducing storage waste.
- Accelerating Model Delivery and Launch. Traditional deployment involves complex dependencies and manual configuration, often taking days. With a composable plugin architecture and standardized templates, users can deploy models in minutes by simply selecting the model and configuring basic parameters.
- Strengthening Management and Observability. Heterogeneous models often lead to fragmented O&M. SMTX AI Platform provides unified management across all locations, utilizing multi-tenancy for resource isolation. It includes API key management, token usage statistics, and full-stack monitoring—from low-level GPU status to high-level inference services.
Versatile Deployment Modes for Diverse Scenarios
To meet the needs of different scales and use cases, the platform offers three flexible deployment options:
- Standalone Deployment: Infrastructure-independent and can be deployed anywhere. Ideal for users looking to validate AI value at minimal cost without modifying existing infrastructure (e.g., without OS reinstallation).
- Bare-metal SKS + AI Platform: Designed for high-concurrency, high-performance scenarios involving large-scale models. By building production-grade SMTX Kubernetes Service (SKS) on bare metal with high-performance persistent storage, it maximizes hardware performance for core business AI services.
- Virtualized SKS + AI Platform: Best for small-scale models, low-concurrency, or DevTest environments. By deploying Kubernetes (SKS) on SmartX virtual machines (ELF), enterprises can reuse existing virtualization pools for elastic scheduling and stable, production-grade management.
Ecosystem Synergy & Trial Support
SmartX is committed to building an open AI ecosystem. It has already completed joint solution validations with partners like Baihai IDP and Fit2Cloud MaxKB, covering the entire workflow from model training and fine-tuning to AI application orchestration and final implementation.
Enterprise users can contact their local SmartX sales representative or reach out via the “Sales Inquiries” to request access and experience a truly simple, flexible, and open AI infrastructure.
Learn more about the SMTX AI Platform and our solutions for AI infrastructure :
SMTX AI Platform: Build AI-Ready Infrastructure with Ease
Introducing SmartX HCI Solution for AI Applications
Accelerate DeepSeek Deployment in Enterprises with SmartX ECP: Solution and Validation
