After deploying Aurora—one of the world's largest supercomputers—we watched brilliant teams wait months for compute access. Not for ideas. For infrastructure.
The same pattern appeared everywhere. At Nvidia, Apple, Tesla, Intel: incredible teams slowed by infrastructure complexity.
The numbers told the story:
We saw a different approach.
Large-scale AI computing is fundamentally just efficient small computers designed to scale. Build the most efficient compute unit. Design it to be heterogeneous. Route workloads to optimal hardware automatically.
That principle became FlexAI.
You run models. We handle infrastructure. Deploy anywhere. Run on any architecture. Infrastructure that gets out of the way.
AI for Everyone, Everywhere.
AI should run everywhere. On every device. In every application. Across any cloud. On any hardware.
The barrier isn't AI capability. It's infrastructure complexity.
We're removing that barrier.
Compute should be fluid. Models should be portable. Deployment should be instant. Costs should be predictable. Utilization should be high.
FlexAI makes infrastructure work the way it should: invisibly. You build models. We handle everything else.
From conferences to celebrations, we're building the future of AI together.
Brijesh brings deep infrastructure expertise, having deployed Aurora, one of the world's largest supercomputers, and managed 50,000+ GPUs at Intel. He previously led teams at NVIDIA, Apple, and Tesla, focusing on scalable AI systems. FlexAI exists because infrastructure should never slow down innovation.
Sundar is a seasoned operations leader with deep expertise in scaling AI infrastructure companies and building high-performance teams across global markets.
Olivier is a leading AI researcher with extensive publications at top ML conferences. He previously led research teams at major tech companies.
You shouldn't configure it, manage it, or optimize it. Build models. Deploy workloads. Infrastructure works in the background.
20-30% GPU utilization wastes resources. We hit 90% through multi-tenancy, intelligent packing, and self-healing infrastructure. Higher utilization means lower costs.
One architecture won't dominate. The best approach uses optimal hardware for each stage—train on NVIDIA, serve on AMD, scale on TPUs. Switch seamlessly.
Every day spent on infrastructure is time not spent improving models. We optimize for deployment speed. Hours, not weeks.
Models work on any hardware. Infrastructure should too. Any cloud. Any chip. One codebase. That's how it should work.
Built by dreamers, engineers, and visionaries who believe AI should empower humanity.
Our engineering team includes PhDs and researchers from top universities who've published groundbreaking papers in machine learning, natural language processing, and computer vision. They're now focused on turning theoretical breakthroughs into practical tools that anyone can use.
60+
Customers
With team members across 25+ countries, we bring diverse perspectives to AI development. This global viewpoint ensures our technology works for everyone, regardless of language, culture, or location.
25+
Countries
Our team has built AI systems at companies like Google, Microsoft, Amazon, and leading startups. We've learned from the best, and now we're creating something even better – AI that truly serves humanity.
15+
Years
Experience
The answer to Nvidia's two-year waitlist.
50%+
Compute Cost Savings
>90%
GPU Utilization
<60s
Job Launch Time
Multi-Cloud
Seamless Deployment
AMD
Optimized inference on MI300 series
Google for Startups
Credits and technical support
Microsoft for Startups
Azure integration with startup pricing
Build the Future of AI Compute
At FlexAI, we're making AI workloads effortless—eliminating infrastructure complexity so developers can focus on innovation. Join us in defining Workload as a Service (WaaS).
One platform. Any cloud. Any hardware. Anywhere.
Get Started with $100 Credit%201.png)
