Private AI Infrastructure Engineering

GPU Smith is an independent engineering firm that specifies, procures, integrates, and validates private AI infrastructure for clients worldwide, ranging from single inference nodes to multi-megawatt GPU clusters and compute halls. The firm works with reference designs based on Nvidia architectures such as HGX B200 systems and 400G InfiniBand fabrics, delivering engagements against written acceptance criteria with an as-built documentation set. Each project includes a disclosed procurement margin and fixed-scope assessments that can be credited toward a subsequent build.

The firm operates under a vendor-neutral model with no reseller quotas or vendor incentives, ensuring recommendations are unbiased by sales targets. They cover six specific disciplines including hardware integration, cluster architecture, and serving optimization, while bringing in partner firms for electrical, mechanical, and thermal engineering under a single statement of work. This structure allows them to coordinate all necessary engineering disciplines through one accountable party for the client.

The company provides fixed-scope engineering assessments that typically take three weeks to deliver, including workload characterization, total cost of ownership analysis, and a reference architecture. If a client proceeds with the build, the assessment fee is credited in full against the build cost. These assessments can also be issued as a no-build recommendation if the analysis determines that renting or other solutions are more appropriate than building private infrastructure.

The firm serves government and regulated enterprises requiring air-gapped or sovereign systems, AI teams with high cloud spend, and investors conducting technical due diligence on datacenter assets. They also handle distributed and edge compute for energy and hardware companies, where power and field service constraints shape the economics alongside hardware choices. Work can be structured under NDA to accommodate specific data boundary constraints.

The firm's headquarters are located at GPU Smith LLC, 3101 Park Boulevard, 1st Floor, Palo Alto, CA 94306, United States, with a secondary business address at 929 Berryessa Road, Suite 20, San Jose, CA 95133, United States. They operate globally and consider engagements worldwide, though their physical presence is in California. The firm's contact phone number is +1 (669) 444-4678 and their email is [email protected].

The firm's pricing model includes a disclosed procurement margin when they purchase hardware for a client, which is explicitly stated in the statement of work. They also offer fixed-scope assessments that can be credited toward a subsequent build. While specific hardware prices vary by market, the firm references street prices for components like NVIDIA H100s and B200s in their published research, noting ranges from $25,000 to $40,000 for new units.

The firm's core services include hardware integration and commissioning of HGX, DGX, and NVL72 systems, as well as InfiniBand and Spectrum-X fabric validation. They also provide cluster architecture sizing, inference build-out from empty rack to first validated token, and serving optimization through quantization and scheduler tuning. Additional services cover datacenter operations, capacity planning, and sovereign air-gapped system design.

The firm's assessment methodology involves deriving topology, node count, and serving stacks from workload models and throughput targets, then configuring TensorRT-LLM, vLLM, and Triton to measured requirements. They validate fabrics port by port against a link budget and ensure rail-optimized IT loads of approximately 100 kW for liquid-ready systems. The goal is to achieve at least 80% target sustained utilization measured at acceptance.

The firm's reference design R-04 outlines a private inference pod with 64 NVIDIA Blackwell accelerators, 12.2 TB HBM3e memory, and 400G InfiniBand NDR rail-optimized IT loads. The system includes 42U IB spine, QM9790, and NDR 400G NVLink switch trays, with PDU specifications of 415 V 3Φ. This design is validated across scales from a single node to a full compute hall.

The firm publishes a GPU Price Index 2026 covering H100, H200, B200, and GB200/GB300 street prices, noting that H100s rent for as little as $1.33 per GPU-hour on marketplaces up to $12.29 on premium hyperscaler instances. They also track manufacturing costs, such as an estimated $6,400 for a B200 GPU, and document the widening gap between list price and street price in their articles.

The firm's website states that owned compute becomes more cost-effective than cloud pricing at sustained load, as per-token cloud costs exceed the amortized cost of owned hardware. They emphasize that their design rationale is based on capital decisions rather than beliefs, and they provide a no-build recommendation as a successful engagement outcome if building is not optimal.

The firm's leadership includes Adrien Laurent as CEO, and they operate as a small, independent firm without a sales development layer. They respond to substantive enquiries within two business days and require four specific lines of information from clients to start an assessment request, including workload details and constraints.

The firm's contact methods include the business email [email protected] and the phone number +1 (669) 444-4678. They also provide a physical address at 929 Berryessa Road, Suite 20, San Jose, CA 95133, United States for assessments. Clients are instructed to open a pre-structured email with specific fields like workload, constraints, timeline, and site jurisdiction to initiate contact.

The official website of Private AI Infrastructure Engineering is gpusmith.com.

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