Rise Union provides full-stack AI infrastructure solutions, enabling end-to-end intelligent support from underlying computing power to upper-layer applications
Through software-defined heterogeneous computing management platform, achieve efficient resource scheduling and intelligent operations to help enterprises accelerate AI innovation
Topology-aware scheduling algorithms providing optimal resource allocation strategies for AI lifecycle
vGPU technology enables fine-grained computing resource slicing, supporting multi-tenant sharing and improving utilization
Unified management of various domestic/international AI accelerators, enabling resource pooling and flexible scheduling
Visual monitoring and automated operations capabilities reduce management costs and improve operational efficiency
AI computing scheduling platform for enterprises, providing unified development environment and resource management
Complete AI development environment supporting mainstream deep learning frameworks for quick project startup
Support multi-team collaborative development with resource isolation and permission management to ensure development environment security
Built-in code and model version management supporting team collaboration and ensuring project traceability
Unified management of AI training and inference tasks with workflow orchestration and monitoring to improve development efficiency
Comprehensive model lifecycle management platform helping enterprises efficiently manage and optimize AI models
Provides unified management and model access capabilities for foundation models in the marketplace, while users can also integrate fine-tuned models
Model evaluation is a key step in model validation. Model optimization teams can customize evaluation datasets to verify the effectiveness of fine-tuned models
One-click deployment of model services based on fine-tuned model files, with quick testing and validation of deployed model services
Support creating model fine-tuning tasks, enabling SFT, LoRA, and full parameter fine-tuning of foundation models based on uploaded training datasets
All-in-one solution designed for enterprise AI computing scenarios, offering out-of-the-box deployment and reduced AI application development costs
Complete deployment and configuration in 15 minutes, ready for immediate use
Support management of various heterogeneous devices with unified scheduling and monitoring
70% improvement in resource utilization, significantly reducing operational costs
Stable support for 1000+ concurrent users, meeting enterprise-level demands
Support distributed training clusters of hundreds of nodes for efficient large model training. A leading internet company using our solution achieved 40% improvement in training efficiency with 85% resource utilization.
Provide high-performance, low-latency model inference services. A financial institution deployed 100+ model services supporting thousands of concurrent requests with over 50% cost reduction.
Provide unified development environment for AI R&D teams. A tech company reduced environment deployment time from 3 days to 30 minutes, significantly improving development efficiency.
Build enterprise-level computing resource pools for resource sharing and unified management. A research institute supporting multiple research groups improved average resource utilization from 30% to 80%.
