AI Infrastructure Startup Funding 2025-2026
In our AI infrastructure market deck, you will find everything you need to understand the market
SUMMARY
We analyzed every publicly disclosed equity or equity-linked round raised by pure-play AI infrastructure companies between July 2025 and June 2026, a 12 months window covering every geography. We only kept rounds of $300K or more, and excluded end-user AI applications, model API products, generic MLOps, generic data tools, and power-only companies outside the compute-and-cluster layer.
Over this period, fundraising in the AI infrastructure market was large but highly concentrated. The dataset includes 27 disclosed deals and $12.53B raised across 24 unique companies.
The AI infrastructure market is being funded less like a broad software market and more like a physical infrastructure buildout. Late-stage rounds, Series C rounds, and growth-equity financings account for 82.5% of total disclosed capital.
Capital concentration is extreme. The top deal alone represents 16.0% of total capital raised, the top 3 deals reach 38.9%, the top 5 reach 56.5%, and the top 10 reach 82.7%.
Megarounds are the baseline in the AI infrastructure market. 22 of 27 disclosed deals are above $50M, 20 are above $100M, and the median round size is $230M.
Monthly funding activity is lumpy rather than smooth. The AI infrastructure market averaged 2.25 deals per month, but August 2025, December 2025, and June 2026 through June 8 had no qualifying disclosed deals.
AI Cluster Cloud dominates the market by capital. The category raised $7.57B, or 60.4% of all disclosed dollars, from only 8 deals.
North America is the broadest geography in the AI infrastructure market, with 19 deals and $7.60B raised. Europe is much narrower but still captures $4.53B because of very large Nscale and Nebius financings.
Early-stage formation is limited. Seed, Series A, and Series B rounds together represent 17.5% of capital, while Series C, Series D+, and Growth Equity rounds represent 82.5%.
Follow-on rounds dominate the AI infrastructure market. Only one disclosed deal in the dataset is classified as first financing, which means visible capital mostly went to companies that had already built technical, customer, or investor credibility.
Strategic ecosystem investors appear repeatedly. NVIDIA, Dell, Nokia, Samsung-related capital, Fidelity, Sequoia Capital, and Insight Partners show up across multiple rounds because supply-chain access, capacity commitments, and market alignment matter as much as cash.
This market map, featured in our AI infrastructure market deck, highlights top companies and startups in the AI infrastructure market
What are all the funding deals in the AI infrastructure market from July 2025 to June 2026?
The table below lists every disclosed equity or equity-linked round raised by pure-play AI infrastructure companies between July 2025 and June 2026. We define the AI infrastructure market as the technologies and services required to run AI training and inference reliably at scale, including AI compute, AI-optimized cloud and cluster platforms, and the networking and storage required to move and serve model data and outputs.
Each row shows the company, what it does, its category, the deal date, the funding stage, the round size, the region, the main investors, and the announcement source. For a wider view of how AI infrastructure fits into the broader compute buildout, we cover it in our AI Infrastructure market report.
| Company | What they do | Category | Date | Stage | Deal size | Region | Main investors | Source |
|---|---|---|---|---|---|---|---|---|
| Armada | Builds modular, full-stack AI infrastructure and modular AI data centers for edge and sovereign deployments | AI Compute Platforms | Jul 2025 | Series A | $131M | North America | Strategic investors; other disclosed investors | Armada |
| FuriosaAI | Develops AI inference chips and compute systems, including the RNGD accelerator | AI Accelerators | Jul 2025 | Series C | $125M | Asia-Pacific | Disclosed round investors | FuriosaAI |
| Baseten | Provides inference infrastructure for deploying and scaling production AI models | AI Compute Platforms | Sep 2025 | Series D+ | $150M | North America | Disclosed round investors | Baseten |
| Nebius | Operates AI cloud infrastructure and GPU capacity for large-scale AI workloads | AI Cluster Cloud | Sep 2025 | Growth Equity | $1,000M | Europe | Disclosed equity investors | Nebius |
| Nscale | AI hyperscaler providing GPU infrastructure, AI data centers, and large-scale AI compute capacity | AI Cluster Cloud | Sep 2025 | Series B | $1,100M | Europe | NVIDIA; Dell; Nokia; Aker ASA; Blue Owl managed funds; Fidelity Management & Research; Point72 | Nscale |
| Modal | AI-native cloud compute platform for running AI, data, and GPU workloads in production | AI Compute Platforms | Sep 2025 | Series B | $87M | North America | Disclosed round investors | Modal |
| Rebellions | Develops AI inference chips and chiplet-based accelerator infrastructure | AI Accelerators | Sep 2025 | Series C | $250M | Asia-Pacific | Arm; Samsung-related capital; other disclosed investors | Rebellions |
| Cerebras Systems | Builds wafer-scale AI processors, AI servers, and full-stack AI infrastructure systems | AI Server Systems | Sep 2025 | Series D+ | $1,100M | North America | Fidelity Management & Research; other disclosed investors | Cerebras |
| Nscale | AI hyperscaler providing GPU infrastructure, AI data centers, and large-scale AI compute capacity | AI Cluster Cloud | Oct 2025 | Growth Equity | $433M | Europe | NVIDIA; Dell; Nokia; Blue Owl managed funds | Nscale |
| Tigris Data | Globally distributed object storage service purpose-built for AI workloads | AI Storage Systems | Oct 2025 | Series A | $25M | North America | Disclosed round investors | Tigris Data |
| Crusoe | Vertically integrated AI factory and AI cloud infrastructure company | AI Cluster Cloud | Oct 2025 | Series D+ | $1,375M | North America | Disclosed round investors | Crusoe |
| Fireworks AI | AI inference cloud for production AI applications and open-model deployment | AI Compute Platforms | Oct 2025 | Series C | $250M | North America | Sequoia Capital; other disclosed investors | Fireworks AI |
| d-Matrix | Builds data-center AI inference compute platforms using in-memory compute | AI Accelerators | Nov 2025 | Series C | $275M | North America | Disclosed round investors | d-Matrix |
| Lambda | AI cloud provider deploying GPU infrastructure and AI factories for hyperscalers, enterprises, and AI labs | AI Cluster Cloud | Nov 2025 | Series D+ | $1,500M | North America | TWG Global; US Innovative Technology Fund; other disclosed investors | Lambda |
| LightSpeed Photonics | Develops optical interconnect technology for AI and HPC data centers | AI Network Fabric | Nov 2025 | Seed | $6.5M | Asia-Pacific | pi Ventures; other disclosed investors | The Economic Times |
| Quadric | Provides processor IP and inference engines for on-device AI chips | AI Accelerators | Jan 2026 | Series C | $30M | North America | Disclosed round investors | Quadric |
| Neurophos | Develops photonic AI chips for exaflop-scale AI compute | AI Accelerators | Jan 2026 | Series A | $110M | North America | Disclosed round investors | PR Newswire |
| Positron AI | Builds energy-efficient AI inference hardware | AI Accelerators | Feb 2026 | Series B | $230M | North America | Disclosed round investors | Business Wire |
| SambaNova | Builds integrated AI infrastructure systems and chips for scalable inference | AI Server Systems | Feb 2026 | Growth Equity | $350M | North America | Samsung-related capital; other disclosed investors | Business Wire |
| Ayar Labs | Builds co-packaged optics and optical interconnects for AI scale-up | AI Network Fabric | Mar 2026 | Series D+ | $500M | North America | NVIDIA; Sequoia Capital; Insight Partners; AMD Ventures-related capital; other disclosed investors | Ayar Labs |
| Nscale | AI hyperscaler providing GPU infrastructure, AI data centers, and large-scale AI compute capacity | AI Cluster Cloud | Mar 2026 | Series C | $2,000M | Europe | NVIDIA; Dell; Nokia; Aker ASA; Point72 | Nscale |
| Gimlet Labs | Develops inference infrastructure software for multi-silicon AI inference clouds | AI Compute Platforms | Mar 2026 | Series A | $80M | North America | Disclosed round investors | TechCrunch |
| Nava | Builds AI cloud infrastructure, GPU compute, and AI data centers across Asia-Pacific | AI Cluster Cloud | Apr 2026 | Series A | $22M | Asia-Pacific | Disclosed round investors | Data Center Dynamics |
| Parasail | AI supercloud for inference and training deployments, especially agent workloads | AI Compute Platforms | Apr 2026 | Series A | $32M | North America | Disclosed round investors | PR Newswire |
| VAST Data | AI data and storage platform and AI operating system for large-scale AI infrastructure | AI Storage Systems | Apr 2026 | Series D+ | $1,000M | North America | NVIDIA; Fidelity Management & Research; Insight Partners; other disclosed investors | VAST Data |
| Panthalassa | Develops autonomous ocean-powered compute nodes designed to house and power AI inference infrastructure at sea | AI Cluster Cloud | May 2026 | Series B | $140M | North America | Disclosed round investors | Business Wire |
| Armada | Builds modular AI infrastructure and AI factory deployments from edge to larger AI data-center systems | AI Compute Platforms | May 2026 | Series B | $230M | North America | Disclosed round investors | PR Newswire |
In our AI infrastructure market deck, we identify pain points entrepreneurs should prioritize
OUR METHODOLOGY TO BUILD THIS TRACKER
We built this AI infrastructure funding tracker by reviewing every publicly disclosed equity or equity-linked round raised by pure-play AI infrastructure companies between July 2025 and June 2026. A company counts as pure-play when more than 80% of its activity is dedicated to the compute, cluster, server, accelerator, networking, or storage layer required to run AI training and inference reliably at scale.
We applied four filters to build the dataset. First, we only included equity rounds and equity-linked financings, so debt, senior notes, grants, and revenue financing are excluded. Second, we only counted rounds of $300K or more. Third, we only kept pure-play AI infrastructure companies. And fourth, every entry had to be confirmed by a direct company announcement, a press release, or a tier-1 media report, with the source URL preserved for every row.
We excluded end-user AI applications, foundation-model API services sold as model products, generic data and analytics tools, generic MLOps, security, compliance, workflow software, and power or grid-only companies unless the funded product directly houses or operates AI compute. The final dataset contains 27 disclosed deals across 24 unique companies, and every average, median, share, and concentration ratio is computed on that disclosed sample. Privately raised rounds that were never publicly announced are necessarily missing, which is a known limitation of any public-only AI infrastructure funding tracker.
How active has fundraising been in the AI infrastructure market?
As of June 2026, fundraising in the AI infrastructure market has been very active on dollars and moderate on deal count. Over the past 12 months, companies raised 27 disclosed equity or equity-linked rounds and $12.53B combined, which works out to 2.25 deals per month.
The number of funded companies is not huge. The 27 disclosed deals were raised by 24 unique companies, which means the AI infrastructure market is active but not broad in the way a software application market might be.
Dollar flow is much larger than deal flow suggests. The AI infrastructure market averaged $1.04B raised per month, but the median month was $475M, which shows how much the average is pulled upward by a few very large rounds.
The monthly cadence was uneven. September 2025 produced 6 deals and $3.69B, while March 2026 produced 3 deals and $2.58B. August 2025, December 2025, and June 2026 through June 8 had no qualifying disclosed deals.
If you’re interested in knowing more about the top startups in this industry, check our market report covering AI infrastructure.
How concentrated has fundraising been in the AI infrastructure market?
As of June 2026, fundraising in the AI infrastructure market is highly concentrated at the top. Over the past 12 months, the largest deal accounts for 16.0% of all capital raised, the top 3 deals reach 38.9%, and the top 5 reach 56.5%.
The top 10 deals absorb 82.7% of disclosed capital in the AI infrastructure market. That means any market map that gives every funded company equal visual weight will overstate fragmentation.
Category concentration makes the point even clearer. AI Cluster Cloud represents only 29.6% of deals, but it captures 60.4% of all capital raised, which gives it the highest capital share to deal share ratio in the dataset.
This concentration means total funding headlines need to be read carefully. In the AI infrastructure market, the most important question is often not how many companies raised, but which companies can finance enough capacity to matter.
How much of the AI infrastructure funding signal is driven by outliers?
As of June 2026, a very large share of the AI infrastructure funding signal is driven by outliers. Over the past 12 months, 22 of 27 disclosed deals were above $50M, and 20 were above $100M.
Rounds under $50M account for only $115.5M in disclosed capital. That is less than 1% of total capital raised, so small rounds are useful for spotting emerging technical directions but weak for explaining capital flow.
The median round size is $230M, while the average round size is $464M. That gap confirms that the AI infrastructure market is shaped by balance-sheet-scale financings rather than a normal distribution of venture rounds.
The top 5 deals alone represent 56.5% of all disclosed dollars. Single-deal inclusion decisions around Nscale, Lambda, Crusoe, Cerebras, and Nebius can materially change any market-size conclusion.
This chart, included in our AI infrastructure market deck, shows why CoreWeave is winning in AI infrastructure
Is the AI infrastructure market broad with many targets, or narrow with few fundable companies?
As of June 2026, the AI infrastructure market is narrow rather than broadly distributed. Over the past 12 months, only 24 unique companies produced 27 disclosed qualifying rounds, and most capital went to a small group of asset-heavy companies.
The market has category breadth, but not equal funding depth. The dataset includes cluster clouds, compute platforms, accelerators, server systems, storage systems, and network fabric companies, yet AI Cluster Cloud alone captures most of the dollars.
Repeat financings also matter. Nscale appears three times in the dataset and accounts for $3.53B, which makes it both a company datapoint and a financing-structure datapoint.
This means the AI infrastructure market should not be interpreted as a long tail of equally fundable startups. It is a market where credibility concentrates around companies with capacity, customer commitments, site access, strategic investors, or hard technical bottleneck claims.
Is AI infrastructure mostly an early-stage formation market or a late-stage scaling market?
As of June 2026, the AI infrastructure market is mostly a late-stage scaling market. Over the past 12 months, late-stage capital, defined as Series C, Series D+, and Growth Equity, represents $10.34B, or 82.5% of disclosed dollars.
Early-stage rounds are present, but they do not explain the market. Seed, Series A, and Series B rounds together account for $2.19B, or 17.5% of total capital raised.
The Seed signal is especially thin. Only one disclosed Seed deal appears in the dataset, LightSpeed Photonics at $6.5M, which shows how little true first-financing activity is visible in public AI infrastructure funding data.
The round labels also show how expensive scaling has become. Series D+ rounds average $937.5M, Growth Equity rounds average $594.3M, and Series C rounds average $488.3M, so the center of gravity is asset deployment rather than company formation.
If you want to learn more about what investors are currently betting on, check out our report on the AI infrastructure market.
Which categories attract the most investor attention in AI infrastructure?
As of June 2026, AI Cluster Cloud and AI Compute Platforms attract the most investor attention by deal count in AI infrastructure. Over the past 12 months, AI Cluster Cloud produced 8 deals, while AI Compute Platforms produced 7 deals.
AI Cluster Cloud is the clearest leader when attention is measured by capital. The category raised $7.57B, or 60.4% of total disclosed funding, because companies like Nscale, Lambda, Crusoe, Nebius, and Panthalassa require very large balance sheets.
AI Compute Platforms look more active by company count than by dollars. The category represents 25.9% of deals but only 7.7% of capital, which suggests these companies are strategically important but less asset-heavy than neoclouds.
AI Accelerators also remain visible. The category produced 6 deals and $1.02B, showing that chip startups are still fundable when they tie the thesis to inference, energy efficiency, photonics, or specialized compute.
This chart, included in our AI infrastructure market deck, shows annual funding in AI infrastructure startups
Which categories attract disproportionately large checks in the AI infrastructure market?
As of June 2026, AI Cluster Cloud attracts the most disproportionately large checks in the AI infrastructure market. Over the past 12 months, the category captured 60.4% of capital from only 29.6% of deals, giving it a capital share to deal share ratio of 2.04.
This is the strongest check-size signal in the dataset. Investors are treating GPU capacity, AI data centers, and AI cloud clusters as the scarcest and most financeable bottleneck in the AI infrastructure market.
AI Server Systems also attracts large checks relative to deal count. The category represents only 7.4% of deals but 11.6% of capital, helped by Cerebras at $1.1B and SambaNova at $350M.
AI Compute Platforms show the opposite pattern. They account for 25.9% of deals but only 7.7% of dollars, which means deal count is a better signal than capital share for that category.
Which geographies matter most for fundraising in the AI infrastructure market?
As of June 2026, North America matters most by breadth in the AI infrastructure market, while Europe matters most by average check size. Over the past 12 months, North America produced 19 deals and $7.60B, while Europe produced 4 deals and $4.53B.
North America captures 70.4% of deals and 60.6% of disclosed capital. It is the deepest geography across cloud, chips, storage, network fabric, server systems, and compute platforms.
Europe captures 36.2% of capital from only 14.8% of deals. That looks strong at the headline level, but it is mostly Nscale plus Nebius rather than a broad European ecosystem.
Asia-Pacific is visible but smaller on dollars. The region produced 4 deals, or 14.8% of the sample, but only $403.5M, or 3.2% of capital.
If you want to identify the opportunities currently emerging in this market, explore our market pitch on AI infrastructure.
Is the AI infrastructure opportunity set broad or concentrated in one hub?
As of June 2026, the AI infrastructure opportunity set is concentrated in a few hubs rather than evenly global. Over the past 12 months, North America, Europe, and Asia-Pacific account for all disclosed qualifying deals and all disclosed capital.
North America is the only region with real category breadth. Its 19 deals span AI Cluster Cloud, AI Compute Platforms, AI Accelerators, AI Server Systems, AI Storage Systems, and AI Network Fabric.
Europe is much more concentrated. Its 4 disclosed deals are all tied to Nebius or Nscale, which means Europe’s apparent strength should be stress-tested at the company level.
Latin America, the Middle East, and Africa have no headquarters represented in the funded pure-play dataset. That does not mean those regions are irrelevant as customers or capital sources, but it does mean company formation and fundraising leadership remained elsewhere during this period.
This chart, included in our AI infrastructure market deck, compares the main business model options for AI cloud infrastructure providers
Is AI infrastructure a market of small experiments or scaled financings?
As of June 2026, AI infrastructure is clearly a market of scaled financings, not small experiments. Over the past 12 months, 22 of 27 disclosed deals were $50M or larger, and 20 were $100M or larger.
The size distribution is unusually top-heavy. There were no disclosed deals below $5M, one deal between $5M and $20M, 4 deals between $20M and $50M, and 22 deals above $50M.
The median round size is $230M, which is unusually high for a startup funding sample. It shows that the minimum credible unit of competition has moved from software-team scale to facility, chip, supply-chain, or fleet scale.
The average round size is $464.1M, but that number is heavily influenced by billion-dollar financings. In the AI infrastructure market, average deal size should be read as a sign of capital intensity, not as a typical round expectation.
If you want to stay on top of the latest trends, risks, and opportunities in this market, check out our market report on AI infrastructure, updated every quarter.
Who are the investors that appear the most in AI infrastructure fundraising?
As of June 2026, the most repeated investors in AI infrastructure fundraising are strategic ecosystem investors and large growth capital providers. NVIDIA appears across Nscale, Ayar Labs, and VAST Data, making it one of the clearest repeated names in the dataset.
Dell and Nokia both appear across multiple Nscale rounds. Their repetition is important because it suggests infrastructure funding is being bundled with hardware, networking, and deployment ecosystem alignment.
Fidelity Management & Research appears in Nscale, Cerebras, and VAST Data, while Insight Partners appears in Ayar Labs and VAST Data. These names show that large financial investors still matter when companies can frame the opportunity at cloud-scale outcomes.
Sequoia Capital appears in Fireworks AI and Ayar Labs, while Samsung-related capital appears in Rebellions and SambaNova. The common pattern is not generic venture exposure, but repeated interest in compute bottlenecks, inference infrastructure, and strategic supply-chain positioning.
One important caveat: round announcements rarely disclose how much each investor personally committed. In the AI infrastructure market, investor repetition should be read as co-participation and ecosystem signal, not as a precise ranking of dollars deployed by investor.
This chart, featured in our AI infrastructure market deck, shows the share of revenue generated by each customer segment in the AI infrastructure market
INSIGHTS
The insights below come from reviewing every disclosed equity or equity-linked round in the AI infrastructure market between July 2025 and June 2026. They are not row-by-row summaries. They are the reusable patterns that kept showing up across the 27-deal dataset, and they are meant to stay useful when reading any future AI infrastructure funding announcement.
- The AI infrastructure market is being funded as an infrastructure buildout, not as a broad early-stage venture market. Series C, Series D+, and Growth Equity rounds represent 82.5% of capital. The center of gravity is asset scaling, not company formation.
- Deal count understates concentration in the AI infrastructure market. AI Cluster Cloud is only 29.6% of disclosed deals but 60.4% of disclosed dollars. The real question is not who raised, but who can finance enough capacity to matter.
- The median round size of $230M changes how the market should be read. A credible AI infrastructure company is often competing at facility, chip, supply-chain, or fleet scale. This is very different from normal software startup funding logic.
- The top 10 deals absorb 82.7% of all disclosed capital. Any market map that gives equal visual weight to every funded company will overstate fragmentation. The market is structurally dominated by balance-sheet-scale rounds.
- The top 5 deals account for 56.5% of disclosed capital. That makes the dataset highly sensitive to inclusion choices around Nscale, Lambda, Crusoe, Cerebras, and Nebius. A single qualification decision can shift the market narrative.
- AI Cluster Cloud has the strongest investor conviction signal. Its capital share to deal share ratio is 2.04, the highest of any category. Investors are treating GPU and data-center capacity as the scarcest bottleneck.
- AI Compute Platforms show the opposite pattern. They represent 25.9% of disclosed deals but only 7.7% of capital. These companies may be strategically important even when their dollar share looks modest.
- AI Accelerators are still fundable despite NVIDIA dominance. Six accelerator deals raised $1.02B, and two server-system deals raised another $1.45B. The strongest thesis has narrowed toward inference, photonics, wafer-scale systems, and energy efficiency.
- Europe’s apparent strength is concentrated, not broad. The region captures 36.2% of capital from only 14.8% of deals, mostly because of Nscale and Nebius. European market strength should therefore be tested company by company.
- Asia-Pacific has credible AI chip and cloud activity, but much smaller round sizes. The region contributes 14.8% of disclosed deals but only 3.2% of capital. The data shows less ability to aggregate billion-dollar infrastructure rounds during this period.
- North America is the deepest geography by breadth. It has 70.4% of deals and 60.6% of capital. More importantly, it has category diversity across cloud, chips, storage, network fabric, server systems, and compute platforms.
- True seed formation is almost absent in the disclosed dataset. Only LightSpeed Photonics appears as a first-financing Seed round. Many credible AI infrastructure companies may need years of incubation before they become visible in funding data.
- Rounds under $50M are useful for detecting technical directions but weak for explaining capital flow. They account for only $115.5M, less than 1% of total disclosed funding. The dollars are overwhelmingly in scale rounds.
- The megaround threshold is no longer exceptional in AI infrastructure. 81.5% of disclosed deals are above $50M, and 74.1% are above $100M. What looks large in generic venture is close to baseline here.
- Storage and network fabric are underrepresented by deal count but strategically important. VAST and Ayar show that once a non-compute bottleneck is accepted as central, it can command cloud-like financing logic.
- The category split implies a hierarchy of investor conviction. Capacity ownership comes first, followed by server and chip systems, then storage and networking bottlenecks, then software abstraction layers. That hierarchy mirrors the physical constraint stack of AI deployment.
- Nscale creates a special distortion in the dataset. One company accounts for three deals and $3.53B. It should be treated both as a company datapoint and as evidence of how infrastructure financing can be staged over time.
- Strategic ecosystem investors matter more in AI infrastructure than in many software markets. NVIDIA, Dell, Nokia, Samsung-related capital, and cloud or data-center partners appear because supply-chain access and go-to-market alignment can be as valuable as cash.
- Investor repetition around Nscale points to ecosystem bundling. When hardware, networking, and infrastructure investors return across sequential rounds, the company is being financed as part of an integrated deployment chain.
- Inference is the most visible workload theme across compute platforms and chips. Baseten, Fireworks AI, Gimlet Labs, Parasail, d-Matrix, Positron AI, Neurophos, Rebellions, Quadric, and SambaNova all point toward a shift from training-only infrastructure to inference economics.
- The inference shift does not make the market less capital intensive. It moves capital intensity into chips, optical links, storage, deployment platforms, and specialized inference clouds. Inference scale still needs physical infrastructure.
- The market splits between “own the asset” and “abstract the asset” strategies. Lambda, Crusoe, Nscale, Nebius, and Nava raise to build capacity. Baseten, Modal, Parasail, Fireworks AI, and Gimlet Labs raise to make that capacity easier to consume.
- The best future signals are not press-release adjectives like “AI-native” or “full stack.” Better evidence includes contracted capacity, chip production volume, customer identity, power or site control, strategic investor repetition, and proof that the product removes a specific scaling bottleneck.
Armada ($131M Series A), FuriosaAI ($125M Series C bridge), Baseten ($150M Series D), Nebius ($1B equity financing), Nscale ($1.1B Series B), Modal ($87M Series B), Rebellions ($250M Series C), Cerebras Systems ($1.1B Series G), Nscale ($433M pre-Series C SAFE), Tigris Data ($25M Series A), Crusoe ($1.375B Series E), Fireworks AI ($250M Series C), d-Matrix ($275M Series C), Lambda ($1.5B+ financing), The Economic Times (LightSpeed Photonics), Quadric ($30M Series C), PR Newswire (Neurophos Series A), Business Wire (Positron AI Series B), Business Wire (SambaNova $350M), Ayar Labs ($500M Series E), Nscale ($2B Series C), TechCrunch (Gimlet Labs Series A), Data Center Dynamics (Nava Series A), PR Newswire (Parasail Series A), VAST Data ($1B Series F), Business Wire (Panthalassa Series B), PR Newswire (Armada Series B)
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