Stelia, the AI acceleration platform, and Polar, Europe’s leader in AI-ready data centers, announced a partnership set to redefine enterprise AI adoption. This collaboration integrates Stelia’s innovative data mobility platform with Polar’s state-of-the-art, sustainable AI-ready data center infrastructure, backed by a recent €500 million investment.
“This partnership removes the complexities of AI implementation,” said Stelia CEO Tobias Hooton. “Beyond facilitating AI adoption; we’re creating innovation potential previously unattainable for most enterprises.”
The new alliance integrates Stelia’s AI ecosystem orchestration with Polar’s growing network of AI-optimized data centers, powered by 100% renewable hydroelectric energy. This combination offers a unique environment for AI teams to eliminate the boundaries to innovation while maintaining the highest standards of security and sustainability.
Polar, emerging from stealth mode just last month, has already demonstrated significant market traction with 100% of its initial data center capacity pre-sold. The company is actively developing several AI-optimized data center projects across Europe, all powered by 100% renewable energy.
Andy Hayes, CEO of Polar, commented: ” We evaluated many providers and Stelia are the only option meeting the performance requirements of AI workloads. Together, we’re creating AI-native infrastructure that simplifies AI deployment while meeting the diverse, growing needs of global enterprises. This is about making advanced AI accessible, secure, and sustainable.”
Also Read: Broadcom Launches VeloRAIN for AI Networking Beyond Data Centers
Enterprise AI Workflows: From Training to Inference
The Stelia-Polar partnership creates a template for enterprise AI, uniquely optimized for both training and inference:
- Seamless Data Mobility for AI Workflows: Stelia’s advanced data mobility platform enables efficient movement of massive datasets and AI models across Polar’s network of data centers. This allows enterprises to:
- Rapidly shift workloads between training and inference environments
- Easily distribute trained models to edge locations for inference
- Quickly aggregate edge data for continuous model improvement
- Optimized Infrastructure for Every AI Stage:
- Training: Leverage Polar’s high-density compute environments, powered by direct liquid cooling, to accelerate complex AI model training.
- Inference: Utilize Polar’s distributed network for low-latency inference across Europe, bringing AI closer to end-users.
- Dynamic Resource Allocation: Stelia‘s platform intelligently orchestrates resources across Polar’s data centers, automatically scaling compute power for intensive training jobs or distributing inference workloads for optimal performance and cost-efficiency.
- Collaborative AI Development: Enable seamless collaboration between AI teams, regardless of location. Share datasets, models, and results across Polar‘s European network, accelerating the entire AI development lifecycle.
- Continuous Learning Pipeline: Establish a feedback loop where inference data from edge locations is efficiently aggregated back to central training facilities, enabling continuous model improvement without complex data management.
- Sustainable AI at Scale: Benefit from Polar’s 100% renewable energy infrastructure for both energy-intensive training and widespread inference operations, maintaining environmental responsibility throughout the AI lifecycle.
SOURCE: PRNewswire
