CLIKA

CLIKA operates in the MLOps (machine learning operations) sector, addressing a critical bottleneck in the artificial intelligence industry: the deployment of AI models. Founded in 2021 by the husband-and-wife team Ben Asaf and Nayul Kim, the company is headquartered in Seoul, South Korea, with a presence in San Jose, CA. The founding resulted from a unique synergy of their respective backgrounds. Asaf, the CTO, previously worked at Mobileye, an Intel-acquired autonomous driving company, where he specialized in automating AI development infrastructure and researched methods to accelerate AI at the Hebrew University. Kim, the CEO, has extensive experience in global marketing and business development, having worked as a digital transformation consultant.

The company's core business revolves around a toolkit that automates the compression and acceleration of AI models. This service is designed for enterprises and government agencies struggling to productionize their AI models efficiently. CLIKA's platform takes a pre-trained AI model—whether for vision, audio, or language—and significantly reduces its size and computational requirements. This is achieved through proprietary techniques like quantization, which downsizes models with minimal impact on accuracy. The key benefit for clients is a substantial reduction in inference costs and the ability to deploy complex AI on a wide range of hardware, from powerful cloud servers to resource-constrained edge and embedded devices. The solution is hardware-agnostic, meaning it works across different types of processors without requiring engineers to rebuild deployment pipelines for each one.

CLIKA's technology has demonstrated the ability to reduce AI model sizes by up to 87% and accelerate processing speeds by 12 times with less than a 1% loss in accuracy. The company serves a diverse client base, including government bodies like an agency in Singapore and global enterprises. Its business model appears to be service-based, where it provides its optimization toolkit to these organizations. The company has secured approximately $1.65 million in funding through several rounds, including a pre-seed round in 2022 and participation in various accelerator programs. Investors include D.CAMP, Kim Gisa Company, In-Q-Tel, and NetApp Excellerator, among others.

Keywords: AI model optimization, MLOps, model compression, edge AI, inference acceleration, hardware-agnostic, TinyAI, AI deployment, deep learning, quantization