Turn AI Infrastructure Innovation into Hyperscaler Design Wins
Data center spending is expected to pass $1 trillion in 2026. It runs through accelerators, memory, networking, photonics, power, cooling, and buildings, but the decisions sit with a small number of operators, architectures, and platform programs. We help suppliers find where their product fits, size the part of the budget they can win, reach the people who decide, and get from a first technical meeting to a design win.[1]
$1T+[1]
Worldwide data center capital spending expected in 2026
Operator spending
$54.6B[2]
Estimated 2026 market for high-bandwidth memory (HBM)
Supplier revenue
$19B+[3]
Datacom optical component revenue in 2025
Supplier revenue
~$1T[4]
AI back-end switch sales forecast for 2026 to 2030 combined
Supplier revenue
$120B[5]
Data center power, cooling, and rack market forecast for 2030
Supplier revenue
Operator spending and supplier revenue overlap, so these figures should not be added together. Figures checked on October 22, 2026.
A trillion-dollar market is not your market
You do not need one percent of data center spending. You need to know which architecture program, which customer, which platform generation, and which buying window your product can win.
- Which part of the infrastructure budget can your technology capture?
- Which architecture generation opens the window for it?
- Which hyperscaler, AI cloud, system maker, or chip partner controls the decision?
- What technical evidence will change that decision?
- What has to happen between an engineering conversation and production volume?
How to start
Send a short request
Tell us the outcome you want through the contact form. We reply within one business day.
Scope it together
One conversation covers the use case, systems, data, team responsibilities, and operating environment.
Review a written proposal
You get deliverables, assumptions, customer inputs, milestones, fees, and how scope changes are handled.
Where the dollars are moving
Every accelerator deployment pulls spending through a chain of supporting technology. Photonics is one strong opportunity inside that chain, alongside memory, networking, power, cooling, and the buildings themselves.
- 1Power and site
- 2Facility
- 3Power delivery and cooling
- 4Compute
- 5Memory and storage
- 6Scale-up network
- 7Scale-out network
- 8Optics and data center interconnect
- 9Software and orchestration
How we help suppliers
“How large is our real market?”
Market and wallet sizing
A market size for your product by account, architecture generation, and deployment type, built from the bottom up.
“Who should we sell to?”
Account prioritization
A ranked list of hyperscalers, AI clouds, system makers, and partners, scored on spending, hiring, standards work, funding, and technology signals.
“Who inside the account matters?”
Buying team and ecosystem mapping
The engineering sponsors, architecture owners, sourcing teams, partners, and executives who have to say yes, and who influences them.
“How do we make our product relevant?”
Design-in positioning
Your value in the numbers hyperscalers judge: performance, power, density, latency, reliability, cost, and ease of deployment, with the benchmark and qualification plan to prove it.
“How do we turn this into revenue?”
Business development and sales execution
Account plans, partner strategy, introductions, meeting preparation, and support from first pilot through design win.
We understand both sides of the design win
Our team has built AI infrastructure products and sold AI infrastructure inside the largest cloud providers. We know what suppliers have to build and how hyperscaler teams decide what to buy.
Photowave specifications are published on Lightelligence's product page.
- Led AI and machine learning go-to-market at AWS for Worldwide Public Sector and Regulated Industries, including the AWS Inferentia and Trainium accelerator chips.
- Worked inside two hyperscalers: AWS, and Microsoft, where we directed Azure Data and AI work with US federal agencies.
- Held a vice president role at Luminous Computing, a photonic AI computing company.
- Advised Lightelligence from 2021 to 2024 on its optical fabric and the launch of Photowave, CXL optical interconnect hardware for disaggregated AI memory.
- Authored AWS whitepapers and contributed to the AWS Well-Architected Machine Learning Lens.
From a leaderboard to an account strategy
The Prospectory AI Infrastructure Leaderboard tracks about 377 companies across compute, memory and packaging, interconnect and photonics, power, cooling, facilities, operators, and enabling technology. It follows capital spending, funding, hiring, patents, standards work, and government grants. We use those signals to answer a better question than who is in the market: who has the problem, the budget, the program, and the timing to be worth pursuing now.[6]
A public signal is not proof of a buying program, and no signal does not mean no activity. We use the signals to set priorities, then confirm them account by account.
Open the leaderboardGo deeper by role
Executives sizing a market
AI Infrastructure Market Map
Where the trillion dollars goes, layer by layer, and which part of it your product can compete for.
Business development and sales leaders
Winning Hyperscaler Design-Ins
The five gates between a first meeting and a design win, and who inside a hyperscaler decides at each one.
Optics and interconnect companies
Photonics Go-to-Market
Where optics create enough system value to replace copper or pluggables, and who has to approve the change.
Memory and CXL companies
AI Memory Wall
Why large models run out of GPU memory, which suppliers that creates room for, and what to prove.
Power, cooling, and facility suppliers
Power and Cooling Go-to-Market
How time to power and rack density became buying criteria, and how to sell into facility design.
Frequently Asked Questions
We help companies that make optics, memory, networking, power, cooling, and rack components sell into hyperscalers, AI clouds, and data center operators. That covers market sizing, account prioritization, mapping who decides, design-in positioning, and business development through to a design win.
Dell'Oro Group expects worldwide data center capital spending to pass $1 trillion in 2026 and $3 trillion by 2030. That is what operators spend, not what any one product category can win, so we size each supplier's market from the accounts and architectures it can realistically serve.
The leaderboard, built on Prospectory, tracks companies across the AI data center supply chain using SEC filings, job boards, standards bodies, grants, and patents. We use it to rank target accounts, follow competitors, and spot spending and hiring changes before a buying program becomes public.
References
Figures checked against these sources on October 22, 2026.
- [1] AI infrastructure buildouts and memory cost inflation drove data center capex higher in 1Q 2026 (Dell'Oro Group, June 2026). https://www.delloro.com/news/ai-infrastructure-buildouts-and-memory-cost-inflation-drove-data-center-capex-higher-in-1q-2026/
- [2] 2026 market outlook: focus on the HBM-led memory supercycle, citing a BofA estimate (SK hynix Newsroom, January 2026). https://news.skhynix.com/en/2026-market-outlook-focus-on-the-hbm-led-memory-supercycle/
- [3] Datacom optical component revenue surpasses $19B in 2025 (Cignal AI, April 2026). https://cignal.ai/2026/04/datacom-optical-component-revenue-surpasses-19b-in-2025/
- [4] AI back-end switch sales to approach $1 trillion over the next five years (Dell'Oro Group, July 2026). https://www.delloro.com/news/ai-back-end-switch-sales-to-approach-1-trillion-over-the-next-five-years/
- [5] Data center physical infrastructure market forecast to reach $120 billion by 2030 (Dell'Oro Group, August 2026). https://www.delloro.com/news/data-center-physical-infrastructure-market-forecast-to-reach-120-billion-by-2030/
- [6] AI Infrastructure Leaderboard (Prospectory, sources dated October 16, 2026). https://prospectory.ai/ai-infrastructure-leaderboard/
Building for the AI infrastructure build-out?
Bring one product and the accounts you want to win. We map where it fits, who decides, and what to do first.