Lessons from DeepSeek: Maximizing Value Without Breaking the Bank

Written by Bret Brasso, CRO at Cerio

The rapid advancement of AI demands robust infrastructure, but does investing in AI always have to be expensive? Recent developments, such as those from DeepSeek, have shown there’s a better way to achieve high-performance AI without excessive costs. 

The AI Investment Challenge 

Traditional AI infrastructure investments have been plagued by inefficiencies—rising costs, wasted resources, and underutilized hardware. Businesses are often forced to compromise between affordability and performance. However, DeepSeek’s recent innovations demonstrate that the ever-increasing cost of AI infrastructure is not the only path forward. 

Optimizing AI Infrastructure Investments 

DeepSeek’s approach—using the equivalent of n-1 or n-2 GPUs that deliver sufficient performance at a much lower cost—has proven transformative. If they can achieve this level of performance without relying on high-end, off-the-shelf systems, why can’t others? The current market model assumes that AI infrastructure, and the associated power and cooling, must remain expensive. DeepSeek has disrupted this notion, proving that cost-efficient alternatives exist. 

The broader technology sector’s recent hit on market values underscores this point. Overinvestment in outdated infrastructure models has become a macroeconomic challenge. This is a wake-up call for the industry: there’s a need to rethink how AI at scale is facilitated and to move towards a more sustainable cost-performance ratio. 

The Power of Composability and Disaggregation 

At Cerio, we’ve taken a fresh approach to composability. Composability has transformed industries, and with Composable Disaggregated Infrastructure (CDI), AI computing follows suit. CDI enables organizations to extract maximum value from their investments while significantly reducing costs. This alternative model aligns with the shift demonstrated by DeepSeek—delivering performance while avoiding unnecessary expenses. 

Stretching Your Existing AI Infrastructure 

Rather than a complete overhaul, optimizing current infrastructure through disaggregation allows businesses to: 

• Dynamically adjust Compute and GPU infrastructure in response to rapidly changing design requirements. 

• Reduce energy consumption and rack space. 

• Allocate investments toward critical AI components, such as GPUs, DPUs, and FPGA. 

• Avoid overpaying for networking and associated infrastructure. 

• Increase operational efficiency with streamlined data center management. 

A Rational Approach to AI Investment 

AI adoption shouldn’t be cost-prohibitive, and it shouldn’t require a crystal ball to imagine what the requirements will be, when it comes time to deploy. By rationalizing AI infrastructure, businesses can invest strategically by prioritizing GPUs, optimizing data center efficiency, and ensuring that every dollar spent delivers real world value. This approach also challenges the outdated assumption that massive infrastructure buildouts are the only option, offering a more agile and cost-effective alternative. 

Why Cerio? 

At Cerio, we help businesses maximize AI infrastructure investments by enabling dynamic, cost-effective, high-performance solutions. Our focus is on delivering evolved, composable systems that challenge outdated models and empower organizations to scale AI intelligently. Whether you’re scaling AI workloads or optimizing existing resources, we provide a smarter, more efficient way to power AI. Talk to us about how Cerio can help you make the most of your AI investment—without unnecessary costs.