Specialized AI and analytics workloads are reshaping infrastructure requirements at a time when the technology needed to support them is becoming increasingly complex to source, engineer, and deploy on predictable timelines. 

For one multinational technology investment company, that complexity became a critical consideration when it needed infrastructure capable of supporting a specialized AI analytics platform. The organization knew what the software needed to accomplish, but determining the right hardware architecture and turning it into a deployment-ready environment presented a much larger challenge. 

Paragon Micro provided the engineering expertise and execution needed to bridge that gap. By bringing infrastructure design, technology sourcing, configuration, and provisioning together, Paragon Micro helped shield the project from the complexities of the hardware ecosystem and created a more predictable path to deployment. 

Executive Snapshot

• Client Type: Technology investment holding company 
• Footprint: More than 200 million users across 35 countries 
• The Challenge: Translate specialized AI analytics requirements into the right infrastructure while maintaining speed and flexibility in a rapidly changing technology landscape 
• The Solution: 12 custom-engineered, GPU-intensive servers configured and provisioned to support approximately 2,400 connected devices 
• The Outcome: Deployment-ready systems that reduced customer-side engineering requirements and helped keep the project moving 
• Solution Areas: Infrastructure design, technology sourcing, engineering, configuration, provisioning, validation, deployment support, and warranty capabilities 

The Challenge

Following an investment in an analytics technology company, the customer needed infrastructure capable of supporting highly specific processing and throughput requirements. For one deployment alone, the environment needed to support approximately 2,400 connected devices across 12 servers. 

Finding the right hardware wasn’t as simple as purchasing standard servers. The AI analytics platform required a specialized, GPU-intensive architecture, and the customer needed to determine which configurations could reliably support the software at scale. 

The customer also needed to move quickly. With a highly specialized technical requirement and multiple infrastructure dependencies standing between design and deployment, it needed a faster path to systems that were available, compatible, and ready to perform. 

The Solution

Faced with both a provisioning challenge and an evolving technology landscape, the customer sought expert engineering support to translate its AI analytics requirements into a scalable infrastructure solution. The project landed with Eugene Kozlovitser, Paragon Micro’s Director of Technology & Operations and a 22-year technology veteran, who quickly began assessing the workload and determining the architecture needed to support it. 

The environment would need to support a high volume of connected devices, creating significant processing and throughput requirements. The AI analytics software also required a GPU-intensive architecture. It wasn’t simply a matter of adding GPUs to standard servers. The hardware had to be sized around the number of devices each system would support and the volume of data the platform needed to process. 

Paragon Micro evaluated those requirements and developed appropriately sized server configurations for different workload levels.  

“We partnered with them to architect the system specifications and conduct a high-level sizing exercise across low, medium, and high-complexity tiers. We then evaluated their functional requirements to prescribe the ideal target architecture.” 

— Eugene Kozlovitser, Director of Technology & Operations, Paragon Micro 

To deliver the necessary compute, storage, and networking capabilities, the purpose-built environment included Dell rack servers configured with dual 6434 processors, 128GB DDR5 RAM, quad RTX 4000 Pro Blackwell GPUs, high-capacity RAID storage, 10/25GbE and 1Gb networking, and Ubuntu 22.04. 

That configuration gave the AI analytics platform the GPU compute density, processing capacity, storage, and network connectivity required to accommodate its workload while providing an architecture that could scale according to device and throughput requirements. 

But designing the architecture was only part of the solution. 

Paragon Micro also took responsibility for the work between design and deployment. Hardware and software configuration, firmware and updates, provisioning, validation, and troubleshooting were completed before shipment, turning individual components into finished systems. 

Bringing those capabilities together also gave the customer greater flexibility as sourcing conditions and technology needs evolved. Rather than managing hardware procurement separately from engineering and then determining how to integrate everything, the customer had one partner coordinating the technology and technical requirements around the desired outcome. 

The completed systems were delivered fully configured and validated, minimizing the work required from the customer’s technical team once they arrived. 

Why Paragon Micro

The customer needed more than access to technology. It needed a partner capable of adapting as conditions changed without passing every sourcing, engineering, or deployment complication back to its internal team. 

Building an internal team that could evaluate available technology, engineer the appropriate solution, configure systems to exact specifications, and prepare them for deployment would have required significant time and investment. Working through multiple vendors could also introduce more handoffs, dependencies, and opportunities for delay. 

Paragon Micro provided an alternative by bringing technology access and engineering execution together. The same partner responsible for understanding the workload could help source the technology, engineer the configuration, prepare the systems, validate the environment, and support deployment. 

That model created a buffer between the customer and the complexities of the hardware ecosystem. By managing sourcing, engineering, configuration, and deployment as one coordinated process, Paragon Micro could navigate changing conditions while keeping the customer focused on the larger AI initiative. 

The result was a purpose-built, plug-and-play environment engineered around the customer’s performance requirements and delivered ready for rapid implementation. Instead of requiring the customer to manage each infrastructure dependency independently, Paragon Micro turned those moving parts into a clearer, more predictable path to deployment. 

“That’s the benefit of having one partner. We can provide the engineering support, deliver the technology you need, and support a multinational rollout without the customer having to coordinate multiple vendors.” 

— Kozlovitser 

The Results

Paragon Micro delivered a purpose-built infrastructure solution that: 

• Eliminated approximately 96 hours of customer-side setup and troubleshooting work across the 12-server deployment 
• Supported approximately 2,400 connected devices or sensors across 12 servers 
• Matched GPU-intensive hardware architecture to the analytics platform’s specific processing and throughput requirements 
• Reduced the hardware research and engineering burden placed on the customer’s internal resources 
• Consolidated technology sourcing, engineering, configuration, and deployment preparation through a single partner 
• Delivered fully configured and validated systems requiring minimal customer-side preparation 
• Helped maintain project momentum despite the complexity surrounding specialized infrastructure requirements 
• Provided an infrastructure approach capable of supporting broader multinational deployment requirements