AI Model Optimization ‘CLIKA’ Secures Seed Investment from Global VCs


AI model optimization platform CLIKA announced that it has attracted seed investment from global strategic investors following its flip to the U.S. The investment amount remains undisclosed.

This investment saw participation from Accenture Ventures, IQT (In-Q-Tel), a non-profit strategic investment organization for the U.S. and allied national security communities, Milemark Capital, a Boston-based deep tech investment firm, and Golden Gate Ventures, a leading Southeast Asian venture capital firm based in the U.S. and Singapore.

CLIKA automatically compresses and edits AI models, transforming them into forms optimized for hardware. This allows the converted models to be stably deployed anywhere, including cloud, on-premise (in-house server), and edge environments. While performance and security are not compromised, inference speed is accelerated.

As AI utilization rapidly increases, AI models are becoming progressively larger, yet actual operating environments are limited and fragmented. CLIKA’s technology, which resolves this gap, was recognized, leading to its first seed investment in the U.S.

CLIKA plans to accelerate B2G and B2B global business development through strategic investments from IQT and Accenture Ventures, key investors in the U.S. Go-To-Market (GTM) strategy.

Tom Lounibos, Global Lead at Accenture Ventures, stated, “Through this investment, we will provide strategic support to deliver CLIKA’s advanced models to global enterprise customers.”

Justin Wilder, Managing Director of IQT Singapore, added, “CLIKA is solving today’s AI challenge of deploying high-performance models in resource-constrained environments. CLIKA’s on-premise optimization toolkit enables reliable AI implementation in real-world settings where control, performance, and integrity are essential.”

Nayul Kim, CEO of CLIKA, said, “Existing solutions are mainly pre-compressed models in API form or manual services. CLIKA’s fully automated solution allows user control, making it a core infrastructure for the era of physical AI that implements real-time intelligence.”

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