VESSL AI Raises $12M to Slash GPU Costs by 80% with Innovative MLOps Platform

VESSL AI raised $12 million in a Series A round to optimize GPU costs for AI development, reducing expenses by up to 80% using hybrid infrastructure.
The platform serves 50 enterprise clients, including Hyundai and TMAP Mobility, and has partnerships with Oracle and Google Cloud.

VESSL AI, a South Korean MLOps platform, has raised $12 million in a Series A funding round to expand its infrastructure aimed at optimizing GPU costs for businesses developing custom large language models (LLMs) and vertical AI agents. The platform, founded in 2020 by Jaeman Kuss An, Jihwan Jay Chun, Intae Ryoo, and Yongseon Sean Lee, leverages hybrid infrastructure, combining on-premise and cloud environments to reduce GPU expenses by up to 80%.

Currently, VESSL AI serves 50 enterprise clients, including Hyundai, LIG Nex1, and TMAP Mobility. Its tech startup clients include Yanolja, Upstage, ScatterLab, and Wrtn.ai. The company has also partnered with Oracle and Google Cloud in the U.S. and boasts a user base of over 2,000 individuals.

“VESSL AI’s multi-cloud strategy enables the use of GPUs from a variety of cloud service providers like AWS, Google Cloud, and Lambda,” CEO An explained. “This system automatically selects the most cost-effective and efficient resources, significantly reducing customer costs.”

VESSL offers four main features: VESSL Run for automating model training, VESSL Serve for real-time deployment, VESSL Pipelines for integrating training and data workflows, and VESSL Cluster for optimizing GPU usage.

The new funding, bringing the total raised to $16.8 million, includes investments from A Ventures, Ubiquitous Investment, Mirae Asset Securities, and others. VESSL AI operates with a team of 35 employees across its offices in South Korea and San Mateo, California.

Edited by Harshajit Sarmah