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Axrail Partners with AWS, Phison to Open Gen AI Lab in Malaysia

KUALA LUMPUR: QL Resources Bhd’s subsidiary, Axrail, which is an Amazon Web Services (AWS) Advanced Tier Services Partner in Malaysia has opened a Generative Artificial Intelligence (Gen AI) Lab in Malaysia and Southwest Asia showcasing cloud and edge solutions to support the growing demand for AI solutions and the nation’s digital economy aspirations.

The Gen AI Lab pools the expertise of AWS, Phison and Axrail in one collaborative hub and it showcases cutting-edge cloud solutions powered by AWS, including those built on Amazon Bedrock, alongside on-premise innovation with Phison’s innovative aiDAPTIV+ technology.

“Gen AI Lab caters to the evolving needs of businesses seeking a fast-tracked and scalable path to AI adoption and positions Axrial at the forefront of delivering comprehensive, end-to-end generative AI solutions for both cloud and on-premise environments,” Axrail said.

Its Founder and Chief Executive Officer (CEO) Kelvin Kok said the company is looking at accelerating AI adoption, especially among Malaysian SMEs, leveraging the upcoming AWS region in Malaysia for data residency, low latency and robust cloud services across Southeast Asia.

“This innovative sandbox will empower businesses to reimagine operations through AI, delivering measurable outcomes and future-proofing their approach,” he said.

Meanwhile, Phison Electronics CEO Datuk KS Phua said the company, together with Axrail will also accelerate Malaysia’s AI digital transformation while providing the added assurance of data confidentiality.

“In the future, Phison will continue working with Axrail to expand cooperation in storage and AI applications,” he added.

Located within Axrail’s 3,000 sq ft Centre of Excellence for AI solutions, the Gen AI Lab fosters responsible experimentation and co-creation of generative AI applications.

The Lab is designed to accelerate businesses’ AI readiness by helping them build capabilities to extract value from data and increase operational efficiency across various functions.

— BERNAMA

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