Ceramic Secures $12M to Enhance Enterprise AI Model Training

San Francisco-based AI infrastructure company Ceramic has raised $12 million in seed funding to accelerate the development of its AI model training platform. The investment round was led by NEA, with participation from IBM, Samsung Next, and Earthshot Ventures. The company plans to use the funds to enhance its technology and expand its enterprise customer base.

Founded by Anna Patterson, former Google VP of Engineering and founder of Gradient Ventures, Ceramic.ai provides a software platform designed to improve the efficiency and scalability of foundation model training. The company’s technology allows enterprises to develop, train, and fine-tune their own generative AI models with greater speed and cost-effectiveness. Unlike conventional AI training methods, Ceramic’s platform is optimized for long-context processing and adaptable to various cluster sizes, making it suitable for large-scale AI training without requiring extensive infrastructure investments.

The increasing adoption of AI has presented significant challenges for enterprises looking to scale their models effectively. Many companies struggle with the high costs and technical complexities associated with building and maintaining AI infrastructure. While tech giants can afford to allocate billions of dollars to proprietary AI training solutions, most businesses lack the necessary resources to optimize and expand their models efficiently. Ceramic aims to bridge this gap by offering an enterprise-ready solution that simplifies AI training and reduces computational expenses.

One of the platform’s key advantages is its ability to train models with long contexts and across multiple cluster configurations, enabling companies to scale their AI initiatives without being constrained by traditional hardware limitations. According to Ceramic, its platform is up to 2.5 times faster than leading AI training solutions when running on NVIDIA H100 GPUs. For large-scale long-context models, Ceramic’s infrastructure provides an alternative to conventional methods, optimizing processing efficiency while maintaining high performance.

The funding round underscores growing investor interest in AI model training solutions that address scalability and cost concerns. Lila Tretikov, Partner and Head of AI Strategy at NEA, emphasized the impact of Ceramic’s innovation, stating that the company has "algorithmically shattered a critical bottleneck in model training," allowing enterprises to scale AI workloads 100 times more efficiently without incurring massive costs or complexity.

With the newly secured funding, Ceramic aims to further enhance its platform and expand its reach among enterprises seeking high-performance AI training solutions. The company’s approach to AI infrastructure could provide businesses with the tools needed to navigate the complexities of large-scale AI deployment, reducing both time and cost barriers in the process.