AI Infrastructure Investment and Due Diligence
Examining SLA verification, cost accounting, and financial modeling for AI compute infrastructure investments.
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Oct 24, 2026
Oct 23, 2026
Oct 20, 2026
- SemiAnalysis SemiAnalysis raises its 2027 data center forecast from 43 GW to 50 GW amid public challenges to its scale. Against expectations closer to 25 GW, the team points to construction already underway, tracked “not even campus level, but building by …
- Jeremie Ontiveros The forecast already incorporates construction delays and gradual capacity ramps, making another blanket haircut potentially duplicative. Jeremie says the team adds one to three quarters where warranted. At the discussed Crusoe site, the model includes under 200 MW rather than …
- Jordan points to more than $1 trillion of signed data center leases as support for the construction outlook. Jeremie emphasizes “binding contracts that cannot be cancelled,” with private operators contributing commitments that public-company …
- Reyk Knuhtsen Modular construction is the team’s central explanation for delivering more capacity despite labor constraints. Reyk contrasts traditional 18-month builds with DayOne’s roughly nine-month timelines. His physical example is a shipping-container-like …
- Jeremie Ontiveros Data center oversupply entering 2028 is a risk Jeremie watches, rather than a formal forecast. If facilities expand faster than chip supply, today’s bottleneck could reverse; he sees that possibility as relevant to semiconductor fab …
- SemiAnalysis SemiAnalysis is raising, not cutting, its 2027 data center forecast—from the 43 gigawatts Brad Gerstner called too aggressive on All-In/BG2 to roughly 50GW in a single year. Gerstner publicly cut the forecast in half, and the episode discussed a roughly 25GW alternative. The team’s response: “There’s a lot of …
- Reyk Knuhtsen The methodology rebuttal is granularity: the model tracks thousands of sites “building by building, permit by permit, power allocation by power allocation,” and uses satellite photos. On moratoriums, Reyk Knuhtsen says they mapped over 400 against data centers in the relevant jurisdictions and found about 10% of the mapped …
- SemiAnalysis External haircuts to the number can amount to double counting, because delays are already built into the estimates. The team adds one to three quarters of delay depending on what they observe, treats sub-12-month timelines as a red flag, and assumes …
- Jeremie Ontiveros The 2027 number rests on trackable leading indicators: over $1 trillion in signed data center leases, plus self-build construction starts rising quarter after quarter. Jeremie Ontiveros points to a waterfall of signals: they predicted an order surge at early-stage constructor Sterling, and track private …
- Reyk Knuhtsen Modular construction is an important reason the team thinks the build-out can happen, compressing traditional 18-month timelines to roughly 6–9 months in cited examples. A modularized power hall can require much less labor than having “20 electricians” stick-build it. Reyk cites Anthropic reference designs, …
- Jeremie Ontiveros The tradeable risk: chips are oversupplied versus data centers today, but the constraint could flip to data center oversupply in 2028. Jeremie’s hedged call is that it’s currently easier to get GPUs than data center megawatts. He says the key watch item is how fast chip …
Oct 5, 2026
- Abhilash Jain SemiAnalysis Consulting bridges AI infrastructure’s technical and financial languages through bespoke engagements lasting from 3–4 weeks to a year. Abhilash Jain calls this the “co-design of technology and finance”: institutional investors may need diligence on a $1–2 billion chip, …
- One engagement modeled global token supply by linking the installed chip base, inference-versus-training allocation, per-GPU throughput, and dollars per million tokens. The difficult part was simulating unreleased chips and models—including potential 10, 15, or 20 trillion-parameter systems—then exposing …
- Custom projects can become scalable research products when clients reveal an unmet need that can be standardized. The data-center model and cloud-AI total-cost-of-ownership work originated in consulting, while the inference simulator moved from internal …
- NeoCloud diligence increasingly determines whether unfamiliar operators can obtain financing and survive contractual downside. Investors examine SLAs, OEM warranties, cluster performance, capex, and opex; Jordan highlights 99.9% expected availability versus below 90% …
- SLA risk compounds because operators may hold 15–20-year data-center leases against five-year GPU contracts, while a single power, cooling, rack, or software failure can still trigger the full customer remedy. Insurance can absorb penalties for an efficiently run operator paying a basis-point premium, but “if you have poor performance, you won’t …
- Build, buy, or partner is a conditional decision driven by time-to-market, compute premiums, technical capability, and access to capital. SemiAnalysis advised one client needing 100 MW within six months to lease capacity; a client willing to wait until 2028–2029 received the …
- Abhilash Jain SemiAnalysis built its consulting arm to bridge AI infrastructure and capital allocation—what Abhilash Jain calls “tech finance co-design.” Dedicated teams turn its 13-14 institutional models and technical network into custom work lasting from three to four weeks up to a year, …
- The clearest example is a global token-supply model delivered as living software rather than a slide deck. It combines the current chip install base and its expected five-year growth, training-versus-inference allocation, throughput per GPU and …
- Strategy work maps changing workloads into product specifications and customer priorities. One memory-and-storage company replays agentic traces to test bandwidth-versus-capacity trade-offs, while a semiconductor vendor with …
- A $1 billion neocloud investment requires both technical proof and commercial benchmarking. SemiAnalysis reviews SLAs, OEM warranties and support, tests clusters, identifies what they are good and bad at, and builds 100- or 180-day …
- SLA structure is financing infrastructure, not contractual housekeeping. As operators expand from hyperscalers and specialists to real-estate developers and family offices, Abhilash’s blunt assessment is that …
- Risk assessment must trace each customer promise through the data center, OEM, hardware and software stack. Reviews can range from three core contracts to L3-L5 readiness and bare-metal failure simulations, because electricity, cooling, racks, …
