Client Background:
A rapidly growing biotechnology company is leveraging artificial intelligence to conduct large-scale genomic data analysis, accelerating the drug development process. Due to the enormous data volumes and computational demands, the company requires high-performance AI computing resources. However, constrained by the scalability and maintenance costs of their internal IT infrastructure, they decided to outsource their AI server hosting needs to a professional hosting service provider.
Project Requirements:
The client sought to host a batch of dedicated AI servers to meet the demands of large-scale data processing and complex AI model training. The hosting service needed to provide high availability, data security, and scalability. Additionally, the client required flexible resource allocation options to handle varying project phases and desired to simplify the daily operations and management of the servers.
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Key1
Hardware Infrastructure:Multiple AI servers equipped with top-tier GPUs (such as NVIDIA A100 or V100) were provided, offering robust parallel computing capabilities. The servers were located in a highly secure and redundant professional data center, ensuring 24/7 availability and data security.
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Key2
Hosting and Maintenance Services: Comprehensive server monitoring, maintenance, and optimization services were included, covering automated security updates, system health checks, and regular performance optimizations. The service team offered round-the-clock technical support and could adjust resources flexibly based on client needs.
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Key3
Data Security and Compliance:The data center complied with industry-standard security certifications (such as ISO 27001) and provided options for encrypted storage and transmission, ensuring the confidentiality and integrity of the client's data. The hosting service also adhered to relevant laws and regulations, safeguarding the client’s compliance in data privacy.
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Key4
Elastic Scalability:The hosting service provider supported on-demand expansion of computing resources based on the client’s project phases. The client could flexibly increase or decrease the number and configuration of servers, ensuring efficient resource utilization.
Rapid Deployment:Within two weeks of signing the contract, server configuration, installation, and system integration were completed, and the client successfully deployed their AI models in the hosted environment.
Performance Improvement:The client’s genomic data analysis speed increased by 4 times, and AI model training time was reduced by 70%.
Simplified Operations:The hosting service effectively reduced the operational burden on the client’s IT team, allowing them to focus on core business development and optimization.
High Availability:The high reliability of the data center ensured uninterrupted system operation, with no disruptions to the client’s project schedule due to infrastructure issues.
Flexible Scalability:During critical stages of drug development, the client was able to quickly scale up the number of servers and computing power, ensuring that the development timeline remained on track.
Client Background:
A leading fintech company was developing an AI-based risk control system to analyze customer transaction data in real-time to identify potential fraudulent activities. The system required high-performance computing capabilities to process massive datasets and complex model training, but the existing infrastructure was insufficient. Therefore, the company decided to acquire dedicated AI servers.
Project Requirements:
The client needed a set of high-performance AI servers to support deep learning model training and inference. The servers needed powerful GPU computing capabilities, high-speed storage, and low-latency network connections to ensure real-time system performance. Additionally, the client wanted the servers to seamlessly integrate into their existing IT environment and support future scalability.
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Key1
Hardware Configuration: Equipped with the latest GPU accelerators, such as NVIDIA A100, providing robust parallel computing power. The servers also featured large-capacity SSD storage to ensure fast data read/write operations, along with high-speed network interfaces to support high bandwidth and low latency.
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Key2
Software Environment:Pre-installed with the deep learning frameworks (like TensorFlow, PyTorch) and AI toolchains required by the client. The system was also configured with optimized CUDA drivers and libraries to fully utilize the GPU’s computational power.
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Key3
System Integration:The project team worked closely with the client's IT department to ensure seamless integration of the servers into the existing network and security systems. Additionally, automated deployment scripts were provided to simplify the deployment and management of AI models.
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Key4
Technical Support and Training: Comprehensive technical support was provided, including initial server debugging, performance optimization, and troubleshooting. The project team also offered customized training to the client's technical team, enabling them to quickly get up to speed with the new equipment and master AI model optimization techniques.
- The servers were successfully delivered and deployed within two weeks, with system integration completed seamlessly.
The client's AI model training speed improved by 5 times, and inference speed increased by 3 times.
The new risk control system could process transaction data in real-time, enhancing the accuracy of potential fraud detection by 20%.
The client expressed high satisfaction with the delivery service and plans to acquire more AI servers in the future to further expand their AI applications.
