New venture combines purpose-built GPU workstations, enterprise AI servers, private large language model deployment, and ongoing infrastructure management to help businesses bring artificial intelligence in-house.
-- Hardware.co, a new provider of custom artificial intelligence hardware and infrastructure solutions, today announced its launch in collaboration with the custom AI software development team at DEV.co. The company aims to simplify the process of designing, deploying, and managing the specialized computing infrastructure businesses need to run artificial intelligence workloads privately, securely, and cost-effectively.
As enterprises accelerate their adoption of private large language models (LLMs), autonomous AI agents, machine learning, and data-intensive applications, the demand for specialized computing infrastructure continues to expand. However, organizations seeking to deploy AI outside traditional public cloud environments often face a fragmented market of hardware vendors, GPU manufacturers, systems integrators, and software consultants.
Hardware.co was established to bridge that gap, providing businesses with a single resource for custom hardware configuration, GPU selection, AI infrastructure architecture, private model deployment, and ongoing technical support.
"Most businesses looking to implement private AI don't want to become experts in GPUs, inference engines, server architecture, or model optimization. They want a system that works, protects their information, and delivers a measurable return on investment," said Nate Nead, CEO of DEV.co and founder of Hardware.co. "Hardware.co is designed to make enterprise-grade AI infrastructure more accessible. We're combining purpose-built hardware with the engineering talent required to actually deploy and operate AI systems. The goal isn't simply to sell servers. It's to deliver complete AI computing solutions that businesses can own and control."
Bringing Private AI Infrastructure Within Reach
Hardware.co's initial focus includes custom GPU workstations, rack-mounted AI servers, on-premises LLM appliances, multi-GPU computing systems, and hybrid infrastructure configurations designed around specific organizational requirements.
Potential applications span financial services, healthcare, legal services, manufacturing, software development, and other industries where data privacy, performance, customization, and predictable operating costs are important considerations.
Rather than recommending standardized configurations for every customer, Hardware.co intends to align hardware specifications with individual workloads, evaluating factors such as model size, memory requirements, concurrent users, inference throughput, data sensitivity, and anticipated growth.
The company's approach also emphasizes flexibility across the rapidly evolving open-weight AI ecosystem. Businesses deploying models from families such as Llama, Qwen, Mistral, and DeepSeek can evaluate infrastructure optimized for their particular applications without relying exclusively on third-party hosted AI services.
"AI infrastructure is becoming a strategic business decision, not just an IT purchasing decision," said Timothy Carter, Chief Revenue Officer at DEV.co. "Companies are increasingly asking whether they should continue paying for cloud-based AI consumption or invest in private infrastructure they can control. The answer depends on utilization, security requirements, workload predictability, and total cost of ownership. Hardware.co gives us an opportunity to help clients evaluate those tradeoffs and implement the right solution, rather than forcing every organization into the same deployment model."
More Than Hardware: An Integrated AI Development Ecosystem
A central component of Hardware.co's strategy is its relationship with DEV.co, which provides custom software engineering, private LLM deployments, retrieval-augmented generation (RAG), AI agent development, and enterprise integrations.
Through this collaboration, customers can pursue end-to-end projects that include hardware procurement and configuration, operating system installation, model serving, vector databases, enterprise application integration, performance optimization, and ongoing maintenance.
The combined capabilities are intended to eliminate the disconnect that frequently occurs when organizations purchase expensive AI hardware without having the internal expertise necessary to make productive use of it.
For example, an investment firm could deploy an on-premises AI system designed to process confidential financial documents, analyze investment opportunities, and support internal research workflows. A law firm could establish a private AI environment for document review, contract analysis, and knowledge retrieval. Manufacturers could configure specialized systems for predictive maintenance, computer vision, quality control, and proprietary data analysis.
Each environment can be engineered around the customer's operational and security requirements, with deployment and governance controls tailored to the use case.
A Long-Term Shift Toward Managed AI Infrastructure
Beyond individual hardware sales, Hardware.co is positioning itself to support organizations throughout the operational life of their AI systems.
As open-weight models become more capable and efficient, businesses will need infrastructure that can adapt to changing model requirements without requiring a complete replacement of their computing environment.
Hardware.co's longer-term service strategy includes infrastructure monitoring, software updates, model migration, performance tuning, security maintenance, and hardware lifecycle planning.
The company believes this combination of physical infrastructure and recurring technical services represents an attractive model for organizations seeking the control of private AI without the expense of building a dedicated internal AI infrastructure team.
"There's a misconception that AI is exclusively a software market," said Samuel Edwards, Chief Marketing Officer at DEV.co. "The physical infrastructure behind AI is equally important, particularly as businesses begin evaluating private deployments and more specialized workloads. Hardware.co is positioned at the intersection of those two markets. We're building a brand around helping companies understand what infrastructure they actually need, why they need it, and how to turn that investment into practical business value."
Supporting the Next Generation of Enterprise AI
The launch comes as businesses reconsider how they acquire and operate AI computing resources. While public cloud platforms offer flexibility and rapid deployment, private and hybrid environments can provide compelling alternatives for organizations with sensitive information, sustained workloads, specialized applications, or greater requirements for infrastructure control.
Hardware.co plans to serve businesses ranging from smaller organizations seeking dedicated AI workstations to enterprises evaluating larger GPU clusters and customized private AI environments.
The company will also emphasize infrastructure designed around real-world usage rather than theoretical peak computing capacity, helping customers avoid unnecessary hardware expenditures while retaining a path for future expansion.
"We believe the future of AI infrastructure will be hybrid, distributed, and increasingly tailored to individual business requirements," added Nead. "Some workloads will always make sense in the cloud. Others will be better served on hardware that an organization owns or controls. Our job is to help clients make that distinction and give them the engineering resources to execute successfully."
About Hardware.co
Hardware.co is a custom AI hardware and infrastructure solutions provider focused on GPU workstations, enterprise AI servers, private LLM systems, and specialized computing environments. Working alongside experienced AI software engineers, the company helps organizations evaluate, configure, deploy, and manage computing infrastructure tailored to artificial intelligence and machine learning applications. Hardware.co serves businesses seeking greater control over AI performance, privacy, scalability, and long-term infrastructure costs.
About DEV.co
DEV.co is a custom software development company specializing in enterprise applications, artificial intelligence, web and mobile development, SaaS platforms, and AI-powered business automation. The company's engineering capabilities include private LLM deployment, AI agent development, retrieval-augmented generation, enterprise integrations, and custom AI systems. DEV.co works with organizations to design, develop, and deploy software solutions tailored to their specific operational requirements.
Contact Info:
Name: Samuel Edwards
Email: Send Email
Organization: Digital.Marketing
Website: https://digital.marketing
Release ID: 89205892
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