The role of corporate use of generative AI has expanded beyond creative creation and automation of routine tasks to support complex decision-making.
Against this backdrop, on-premise is now attracting renewed attention.

To enable AI to make decisions, sensitive information needs to be learned, and cloud operations always carry a risk of leakage.
On-premise AI and edge AI can be used without exposing sensitive information outside the company, and can also solve latency problems inherent to cloud computing and high costs due to pay-as-you-go billing.
Moreover, on-premise offers stable performance for tasks that require real-time processing and low latency.

However, there are challenges to its implementation.
On-premise requires individual design, and the initial cost tends to skyrocket, making it difficult for many companies to take the first step.

What we would like to focus on here is a hardware solution for utilizing interactive generative AI on-premise.
This solution provides a pre-validated environment that combines AI software stacks on a GPU-equipped server,
This allows you to get up and running in a short period of time and maximize the power of generative AI while adhering to security policies and compliance.

The AI chatbot has already proven itself in the manufacturing industry, streamlining complex inquiries and achieving a response accuracy of 93%.
The company has also been able to reduce maintenance costs by analyzing legacy COBOL languages and automating their conversion to Java.

The report explains the current trend that is generating a return to on-premise as the role of generative AI expands.
Details of solutions that realize cost-effective on-premise AI infrastructure and,
specific use cases can be reviewed, please contact us for a consultation.