New
platform lets Malaysian organisations tap leading AI models through one
OpenAI-compatible API, helping them scale AI adoption with stronger
governance, security, and cost control.
KUALA LUMPUR, MALAYSIA -
Media OutReach Newswire
- 20 August 2026 - ExcelScale has officially launched its unified AI
infrastructure platform in Malaysia, giving organisations access to more
than 100 leading AI models through a single OpenAI-compatible API. The
platform addresses a challenge that has become increasingly familiar to
Malaysian enterprises moving AI beyond pilot projects: it is no longer
difficult to access AI models, but it is difficult to integrate them
securely and manageably at scale, with separate provider accounts, APIs,
billing systems, and governance requirements adding complexity just as
businesses try to expand adoption.
As Malaysian organisations extend AI use across software development,
research, content production, data analysis and internal workflows, many
are managing multiple AI providers at once. This gives them greater
choice, but it also raises new challenges around interoperability,
governance, and operational oversight as adoption spreads across more
teams and functions.
"Enterprise AI has reached a stage where access is no longer the main
barrier. The greater challenge is bringing different AI capabilities
together in a way that stays practical, secure, and manageable for the
business," said Mr Todd Abraham, General Manager of ExcelScale.
"The next stage of enterprise AI won't be defined by how many models
organisations can access, but by how effectively they can integrate and
manage them. Businesses want the flexibility to choose the right model
for each task without maintaining a separate technical environment every
time. ExcelScale was built to provide that consistent foundation, so
teams can focus on building useful AI applications instead of managing
fragmented systems."
Through a standardised API, organisations could connect to models
supporting text generation, visual recognition, voice synthesis, video
creation, and data analysis without rebuilding their integrations for
each provider, letting technical teams choose models by workload while
keeping a consistent development and deployment process. Enterprise
features including access controls, API key management, configurable
model permissions, Virtual Private Cloud deployment options and usage
monitoring help businesses manage AI services more consistently, while a
centralised dashboard gives oversight of API requests, token
consumption, and costs.
For businesses, this cuts the need to manage multiple disconnected
systems as AI initiatives grow, freeing up time spent maintaining
infrastructure for developing applications that support productivity,
innovation, and operational improvement.
"As AI becomes part of everyday business operations, organisations need
infrastructure that can evolve alongside the technology. Our vision is
to help businesses adopt AI with greater clarity and control," said Mr
Todd.
"By simplifying the layer between organisations and the models they use,
we hope to make it easier for more enterprises to turn AI capabilities
into practical, sustainable business applications."