SUSE Launches SUSE AI: Facilitates Development Of AI Generative Applications

JAKARTA - SISE, an innovative, open and secure company solution provider, announced the availability of SUSE AI, a platform to implement and run the Generative AI (GenAI) application.

As an integrated cloud native solution, SUSE AI allows access to large management models (LLMs), and gives companies complete control over their AI solutions with freedom and data sovereignty.

SUSE AI is developed with input from the SUSE AI Initial Access Program, which involves customers and partners with a GenAI expert from SUSE, to create a basis for a safe and obedient generative AI within the company.

"AI has tremendous potential, but without adequate attention, AI can also cause harm and damage reputation," said Abhinav Puri, Vice President of Portfolio Solutions in SUSE in a written statement quoted Tuesday, November 26.

Abhinav also said that SUSE AI is here to answer the challenges of security and compliance within the company, while allowing companies to run private GenAI solutions easily.

While the value and need for GenAI is increasingly visible, we see many customers facing the risk of compliance. The SUSE approach to AI, which is manifested in SUSE AI solutions and the SUSE AI Initial Access Program, helps customers overcome these challenges," he continued.

The advantages of SUSE AI include:

Well-designed security: SUSE AI provides security and certification at the level of software infrastructure and tools that provide zero trust security, templates, and playbooks for compliance.

Trust from all aspects: With SUSE AI, customers can rely on their AI solutions - trust platform security, believe that the resulting data is accurate, and believe that their customers' personal data and IP are kept confidential.

Options: SUSE AI provides customers with options by providing a secure platform where they can choose AI components. Customers have complete control over platform optimization and development as well as flexibility in selecting and implementing large language models (LLM).