Ceramic.ai recently emerged from stealth with software for foundation model training infrastructure, enabling enterprises to build and fine-tune their generative AI models more efficiently. To support its rapid growth and ongoing development, Ceramic.ai secured $12 million in seed funding from NEA, IBM, Samsung Next, Earthshot Ventures, and Alumni Ventures. This funding is advancing product development, scaling the platform, and expanding Ceramic.ai’s enterprise customer base to meet growing demand.
Launched by Anna Patterson, former Google VP of Engineering and Gradient Ventures founder, Ceramic.ai improves AI model training speed and cost-efficiency. It offers up to a 2.5x performance boost, accelerated by NVIDIA, over current state-of-the-art platforms.
The current AI infrastructure can scale up to 10 times but not 100, so proper exponential growth demands a complete redesign. Ceramic.ai addresses this gap by providing an enterprise-ready platform that isn’t just faster but fundamentally more scalable to power the next generation of AI, dramatically reducing the complexity and cost of AI model training.
The company’s platform’s model can train with extended contexts and any cluster size, enabling enterprises to develop, train, and scale their AI models faster than traditional methods. And for smaller models, Ceramic.ai is up to 2.5x faster on NVIDIA H100 GPUs than current state-of-the-art platforms, and for large-scale long-context models, Ceramic.ai is the only viable choice for fast training.
Ceramic.ai has created a comprehensive platform that addresses the core challenges of enterprise AI deployment:
1.) Speed and Efficiency – Ceramic.ai’s training infrastructure delivers up to 2.5x higher efficiency than open-source stacks, cutting down training costs while improving model performance.
2.) Exclusive Long-Context Training Capability – Ceramic.ai is the only platform that can train large models on long-context data, providing unrivaled quality and performance. The company outperforms all reported benchmarks for long-context model training, maintaining high efficiency even for 70+ billion parameter models.
3.) Superior Reasoning Model Performance – Ceramic trained a reasoning model for problem-solving and achieved an exact match Pass@1 score on GSM8K of 92%, tuning Meta’s Llama70B 3.3 base model up from 78% and outperforming DeepSeek’s R1 84%.
4.) Optimized Data Processing – Ceramic re-orders training data, ensuring each micro-batch is aligned by topic. Current approaches either mask away other documents, losing the benefit of longer context length or pay attention to irrelevant documents, learning bad habits. By re-ordering training data so it comes in 64k or 128k contexts, all on the same topic, we increase the number of data points where attention can learn quadratically.
Created by a team of experts in large-scale infrastructure, Ceramic.ai has already helped show enterprises reduce costs and improve model training efficiency in early trials. And they are partnering with Lambda, AWS and others for accelerated training.
KEY QUOTES:
“In the midst of a surge in AI adoption, too many companies are still hindered by barriers to scale – from prohibitive costs to limited infrastructure. We’re democratizing access to high-performance AI infrastructure so companies can navigate the complexity of AI training without spending hundreds of millions in research and engineering resources. But the shift to enterprise AI isn’t just about better tools – it’s about changing how businesses work. If AI adoption were a baseball game, we’d still be singing the national anthem.”
– Anna Patterson, founder and CEO of Ceramic.ai
“Ceramic.ai is a game-changer for AI developers and enterprises seeking increased efficiency and superior price-performance. Combined, our offerings provide customers with an accelerated full-stack solution, validated and backed by both infrastructure and model expertise. This enables customers to achieve faster outcomes, reduced development costs, and higher-quality solutions.”
– Sam Khosroshahi, VP, BD & Strategic Pursuits I AI & Machine Learning at Lambda
“AI’s meteoric ascent has been like a rocket tethered to a horse-drawn carriage – until now. Anna and her team at Ceramic.ai have algorithmically shattered a critical bottleneck in model training, making it faster, more efficient, and scalable. With Ceramic, companies can scale their already massive AI training workloads 100x – without the corresponding surge in cost or complexity.”
– Lila Tretikov, Partner and Head of AI Strategy, NEA
“Our investment in Ceramic demonstrates how IBM drives innovation and solidifies partnerships in highly strategic areas. We are thrilled to collaborate with Ceramic to address a critical need to reduce AI compute costs, making training more efficient and accessible.”
– Emily Fontaine, Vice President, IBM Global Head of Venture Capital
