Funding
Funding not disclosed
Founders
Product
Problem
Training and deploying AI models often requires extensive compute resources and long iteration cycles, leading to high costs and delayed product releases. Teams must adapt their pipelines or modify model architectures to achieve performance gains, which adds complexity and slows innovation.
Solution
Eury offers a platform that accelerates AI model training by up to 20× and inference by up to 3× without altering the underlying model architecture. The service is model‑agnostic, supporting large language models, vision models, text, and multimodal architectures, and works for both training from scratch and fine‑tuning pre‑trained models. Integration is achieved through a zero‑friction layer that plugs into existing pipelines, preserving existing code and workflows. By reducing compute time, Eury lowers operational costs and enables faster experimentation and product shipping. The platform also provides optimized inference pathways for models trained on Eury or imported from external sources.
Target Audience
Primary customers are AI development teams, data science groups, and machine‑learning engineering departments that need to scale model training and inference while controlling compute costs.
Features
- Model‑agnostic acceleration that supports LLMs, image, text, and multimodal models
- Zero‑friction integration requiring no changes to existing model architecture or code
- Up to 20× faster training, compressing weeks of compute into hours
- Up to 3× faster inference for both native and imported models
- Supports training from scratch and fine‑tuning of pre‑trained models
- Cloud‑based compute infrastructure that reduces on‑premise hardware requirements