EX-99.1 2 dboralarcacq1_ex99-1.htm EXHIBIT 99.1

 

Exhibit 99.1

 

 

A Next - Generation AI Infrastructure Provider April 2026 Exascale Labs

 

 

 

 

IMPORTANT INFORMATION; CONFIDENTIALITY; TESTING - THE - WATERS COMMUNICATION This presentation (the “Presentation”) has been prepared, and is being provided, by Exascale Labs Inc., a Delaware corporation (the “Company”) for informational purposes only, to assist certain institutional investors in evaluating a proposed business combination transaction (the “Business Combination,” and together with the other transactions contemplated by the Business Combination, the “Proposed Transactions”) involving D. Boral ARC Acquisition I Corp., a British Virgin Islands business company (“BCAR”), the Company, D. Boral ARC Merger Corporation, a Delaware corporation and a direct, wholly owned subsidiary of BCAR (“PubCo”) and D. Boral Arc Merger Sub Inc., a Delaware corporation and a direct, wholly owned subsidiary of BCAR (“Merger Sub”). This Presentation is being provided on a confidential basis to a limited number of persons who are reasonably believed to be either “qualified institutional buyers” as defined in Rule 144 A under the Securities Act of 1933, as amended (the “Securities Act”), or institutional “accredited investors” as defined in Rule 501 under the Securities Act. By accepting this Presentation, the recipient agrees (i) to keep the information contained herein confidential and (ii) not to distribute, reproduce or otherwise make this Presentation available, in whole or in part, to any other person. This Presentation constitutes a “testing - the - waters” communication within the meaning of Rule 163 B under the Securities Act. This Presentation does not constitute an offer to sell or the solicitation of an offer to buy any securities, nor shall there be any offer, solicitation or sale of securities in any jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of such jurisdiction. Any offering of securities in connection with the Proposed Transactions will be made solely by means of a registration statement on Form S - 4 (the “Registration Statement”) to be filed with the U. S. Securities and Exchange Commission (the “SEC”), which will include a proxy statement/prospectus. Investors and security holders are urged to read the Registration Statement, including the proxy statement/prospectus contained therein, and any other relevant documents filed with the SEC when they become available because they will contain important information about the Company, BCAR, PubCo and the Proposed Transactions. When available, such documents may be obtained free of charge from the SEC’s website at www. sec. gov. The information contained in this Presentation is preliminary in nature, subject to change, and does not purport to be complete or all - inclusive. The information herein is qualified in its entirety by reference to the Registration Statement when and if it becomes effective. No representation or warranty, express or implied, is made as to the fairness, accuracy or completeness of the information contained herein, and none of the Company, BCAR or PubCo or any of their respective affiliates, advisors or representatives shall have any liability for any loss arising from the use of this Presentation or its contents. FORWARD - LOOKING STATEMENTS This Presentation contains “forward - looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995. These statements include, but are not limited to, statements regarding the Proposed Transactions, future financial and operating results, projections, market opportunities and growth strategies. Forward - looking statements are subject to risks, uncertainties and assumptions, many of which are beyond the control of the Company and BCAR. Actual results may differ materially from those expressed or implied by such forward - looking statements. Factors that could cause such differences include, but are not limited to, those that will be described in the Registration Statement and other filings with the SEC. Neither the Company nor BCAR undertakes any obligation to update any forward - looking statements, except as required by law. Disclaimer 2

 

 

 

 

MARKET AND INDUSTRY DATA This Presentation contains estimates, projections and other information concerning the Company’s industry, market size and growth, market position, illustrative participation levels and competitive landscape based on information from third - party sources and the Company’s own internal estimates and research. Market and industry data used in this Presentation have been obtained from sources believed to be reliable, including industry publications, reports by market research firms and other publicly available information. However, such data involve a number of assumptions and limitations, and neither the Company nor any other party has independently verified such information. The Company’s internal estimates are based on management’s knowledge of the industry, historical experience, publicly available information and other assumptions believed to be reasonable under the circumstances. However, such estimates have not been verified by any independent source and are subject to change. Forecasts and projections relating to the industry and markets in which the Company operates are inherently uncertain and are subject to a variety of risks and uncertainties, including those that will be described in the Company’s filings with the SEC, when available. Actual results may differ materially from those expressed or implied in such estimates and projections. While the Company believes that the market and industry data included in this Presentation are generally reliable, the Company makes no representation or warranty as to the accuracy or completeness of such data. Accordingly, undue reliance should not be placed on such information. USE OF PROJECTIONS This Presentation may include certain financial forecasts and projections. Such projections are forward - looking statements and are based on assumptions that are inherently uncertain and subject to significant business, economic and competitive risks and uncertainties. There can be no assurance that such projections will be realized, and actual results may differ materially. The inclusion of such projections should not be regarded as a representation that such results will be achieved. NO DUTY TO UPDATE; NO RELIANCE The information contained herein speaks only as of the date hereof. Neither the Company nor BCAR assumes any obligation to update or revise this Presentation. Recipients should conduct their own independent investigation and analysis of the Company, BCAR and the Proposed Transactions and should not rely solely on the information contained herein. Disclaimer (continued) 3

 

 

 

 

Transaction Overview

 

 

 

 

Voting (%) Proposed Transaction Overview (minimum redemption) 5 ($ in millions, except share price) Valuation ‒ Exascale pre - money valuation of $500M ‒ Transaction implies $632M pro forma enterprise value Financing ‒ Assumes no additional PIPE financing ‒ Assumes 0% redemptions from D. Boral ARC Acquisition I Corp.’s $280.0M cash in trust Structure ‒ Exascale securityholders to rollover 100% of their equity and are expected to hold approximately 54.8% of the outstanding pro forma equity 91.2 Shares Outstanding (Millions) $10.0 Share Price $912.0 Implied Equity Value ($280.0) (-) Pro Forma Net Cash $632.0 Implied Enterprise Value Sources $500.0 Exascale Rollover Equity $280.0 SPAC Cash in Trust $780.0 Total Sources Uses $500.0 Exascale Rollover Equity $280.0 Cash to Exascale Balance Sheet $780.0 Total Uses Transaction Highlights Pro Forma Valuation (1)(2) Sources and Uses (3) Pro Forma Ownership ($ in millions) 94% 54.8% 50.0 Exascale Existing Securityholders 2% 14.5% 13.2 Sponsor and Representative Shareholders (4) 4% 30.7% 28.0 SPAC Shareholders ▪ Assumptions: (1) No redemptions (0%) for illustrative purposes only; actual results may differ materially). (2) Does not include the shares issuable upon exercise of outstanding warrants. (3) Example does not include transaction e xpe nse assumptions. (4) Includes 12,000,000 founder shares and 200,000 private placement shares issued to the Sponsor and 1,000,000 shares issued to D. Boral Capital at the clos ing of the IPO ▪ Note: Pursuant to the Business Combination Agreement, BCAR agreed to cause PubCo to receive an amount of at least $5,000,000 in any combination of cash, cash in the trust account, a PIPE, an equity line of cr edit, or third - party financing (the “Minimum Cash Financing”). As of the date of this presentation, BCAR has not secured financing for the Minimum Cash Financing. ▪ Note: The valuation described herein was determined through negotiations between the parties and was not based on a third - party valua tion or fairness opinion. Shares (Millions) Ownership (%)

 

 

 

 

Voting (%) Proposed Transaction Overview (maximum redemption) 6 ($ in millions, except share price) Valuation ‒ Exascale pre - money valuation of $500M ‒ Transaction implies $632M pro forma enterprise value Financing ‒ Assumes no additional PIPE financing ‒ Assumes 100% redemptions from D. Boral ARC Acquisition I Corp.’s $280.0M cash in trust Structure ‒ Exascale securityholders to rollover 100% of their equity and are expected to hold approximately 79.1% of the outstanding pro forma equity 63.2 Shares Outstanding (Millions) $10.0 Share Price $632.0 Implied Equity Value $0 (-) Pro Forma Net Cash $632.0 Implied Enterprise Value Sources $500.0 Exascale Rollover Equity $0 SPAC Cash in Trust $500.0 Total Sources Uses $500.0 Exascale Rollover Equity $0 Cash to Exascale Balance Sheet $500.0 Total Uses Transaction Highlights Pro Forma Valuation (1)(2) Sources and Uses (3) Pro Forma Ownership ($ in millions) 98% 79.1% 50.0 Exascale Existing Securityholders 2% 20.9% 13.2 Sponsor and Representative Shareholders (4) Shares (Millions) Ownership (%) ▪ Assumptions: (1) Full redemptions (100%) for illustrative purposes only; actual results may differ materially). (2) Does not include the shares issuable upon exercise of outstanding warrants. (3) Example does not include transaction e xpe nse assumptions. (4) Includes 12,000,000 founder shares and 200,000 private placement shares issued to the Sponsor and 1,000,000 shares issued to D. Boral Capital at the closing of the IPO ▪ Note: Pursuant to the Business Combination Agreement, BCAR agreed to cause PubCo to receive an amount of at least $5,000,000 in any combination of cash, cash in the trust account, a PIPE, an equity line of cr edit, or third - party financing (the “Minimum Cash Financing”). As of the date of this presentation, BCAR has not secured financing for the Minimum Cash Financing. ▪ Note: The valuation described herein was determined through negotiations between the parties and was not based on a third - party valuat ion or fairness opinion.

 

 

 

 

Business Overview

 

 

 

 

Exascale Profile 8 Who We Are Exascale Labs is a next - generation AI infrastructure provider. What We Do We architect, deploy, and operate the critical infrastructure required for high performance AI computing. Our Edge While others compete on capital, we compete on technology and engineering execution. Exascale is designed to deliver megawatts of capacity on schedule.

 

 

 

 

Recurring Compute Revenue with Infrastructure Upside 9 GPU as a Service (GaaS) Infrastructure Solutions GPU cluster management for AIDC operators Modular data center, liquid cooling, HVDC/SST, energy storage solutions (1) Project - based commercial structure with potential expansion as new offerings reach revenue Contracted compute creates a recurring revenue base and infrastructure deployments drive higher - value engagements and customer expansion. Reserved / on - demand Al compute Three months to three years engagements Recurring, high - visibility revenue (1) Modular data center, advanced liquid cooling, HVDC power, and energy storage solutions that management believes are ready for co mmercial engagement but have not generated revenue to date.

 

 

 

 

Rapid growth across enterprise demand and Al infrastructure deployment. (1) Growth and Operational Snapshot 10 22 Enterprise Customers 5.3x (2) FY2025 Revenue vs FY2024 12 Countries with Active Customers US | Canada | UK | Hungary | Poland | Italy | South Korea | Singapore | India | Malaysia | Hong Kong | Australia 92% (3) Customer Retention Rate FY2024 → FY2025 $300K (4) Avg Revenue per Customer 95.5% GPU Utilization (1) Metrics as of December 2025 unless specified otherwise. (2) Reflects the ratio of total revenue of approximately $7.0 million fo r the fiscal year ended June 30, 2025 to total revenue of approximately $1.3 million for the fiscal year ended June 30, 2024, representing an increase of approximately 431.8%. (3) Calculated as the number of FY2024 enterprise customers that continued to generate revenue in FY2025 (11 of 12). (4) Annualized average revenue per enterprise customer based on the six months ended December 31, 2025, up from approximately $140,000 on th e s ame basis for the prior - year period. Annualized, H1 FY25 → H1 FY26

 

 

 

 

Exascale believes its model differs from traditional hyperscalers and finance - driven neocloud models in its emphasis on architecture control, systems integration and asset - light deployment. Exascale positions itself as an implementation partner. Exascale's Positioning in AI Infrastructure 11 (1) Industry perspectives. Sources: Bloomberg (Dec. 2025); S&P Global (Dec. 2025); Deloitte (June 2025); Reuters (March 2026). Hyperscalers General - Purpose Infrastructure Massive Owned Balance Sheets Long Development Cycles Infrastructure as Internal Capability Neoclouds GPU Asset Aggregators Capital - Intensive Scaling Third - Party Infrastructure Reliance Exposure to Supply & Power Constraints The Turnkey Solution Provider Architecture Control Asset Light Deployment Enabling Third - Party AI Deployments Industry reports suggest that t he bottleneck in AI is no longer chips or capital alone, but deployment capacity (1).

 

 

 

 

From buyer outcomes to infrastructure characteristics. A Different Approach to AI Infrastructure Deployment 12 Faster Time to Revenue Proprietary optimization software designed to improve GPU utilization and reliability in selected configurations — enabling customers to generate returns sooner. Lower Execution Risk Exascale's team brings deep operating experience across cloud computing, AI infrastructure, and high - density data center deployment. Simpler, Future - Ready Power Architecture Design, deploy, and operate Modular Data Centers with SST - based HVDC and High - Density Liquid Cooling to support shorter deployment timelines and capital - efficient scaling. More Predictable, Capital - Efficient Scaling Asset - light, modular - first model enables phased CapEx aligned to actual demand — no overbuilding, no stranded capital. (1) Capability descriptions above reflect specifications and testing provided by third - party technology suppliers selected by Ex ascale. Such specifications and testing have not been independently verified by Exascale. Actual performance in Exascale deployments is design - and configuration - dependent and may vary materially based on system specification s, integration, and operating conditions. INFRASTRUCTURE EDGE · MDC + HVDC / SST STACK The selected technology stack is designed for (1) : Faster Builds Modular construction designed to compress site timelines. Modular DC Lower Losses HVDC architecture designed to reduce energy conversion losses. HVDC / SST More Density Compact distribution designed to reclaim floor space for revenue racks. HVDC / SST Faster Install Simpler power systems designed to accelerate install and commissioning. HVDC / SST Less Copper HVDC distribution designed to reduce copper vs low - voltage AC. HVDC / SST Higher Efficiency Solid - State Transformers designed for high conversion efficiency. HVDC / SST

 

 

 

 

$ 68 $ 479 $ 770 $ 1,171 $ 1,442 $ 2,160 $ 2,242 $ 3,262 $ 3,545 Q4 2023 Q1 2024 Q2 2024 Q3 2024 Q4 2024 Q1 2025 Q2 2025 Q3 2025 Q4 2025 $ 3 00M Qualified Pipeline (1) $ 6.8M Six Months Revenue Ended Dec 2025 (GAAP) $7.0 M FY2025 Revenue (GAAP) ($ in thousands, calendar quarters) – GaaS generates immediate cash flow and proves our ability to operate high - performance clusters at scale. – Infrastructure solutions may drive higher revenue and margins. + 64 % average quarterly growth Dec 2025 quarterly revenue ≈ 52x Dec 2023; FY25 revenue at 5.3x FY24 level (GAAP) GaaS provides recurring revenue today. Infrastructure solutions unlock higher - margin growth as the AI buildout accelerates. Accelerating Revenue with Built - In Expansion 13 Exascale Revenue Growth Since Q4 2023 Illustrative Revenue Mix Evolution (2) Audited Revenue Growth and Strong Pipeline Continued Revenue Diversification Rationale GPU as a Service Infrastructure Solutions Current (3) GaaS - Led Over Time GaaS Infrastructure Illustrative representation of strategic trajectory; not a financial forecast. (1) N on - binding, no assurance of conversion, not a financial forecast. (2) Current Infrastructure Solutions revenue reflects revenue - generating service offerings, including GPU cluster management and ope rational services. Certain other Infrastructure Solutions offerings discussed elsewhere in this presentation are not reflected in current revenu e. (3) "Current" reflects the Company's revenue composition as of the date of this presentation.

 

 

 

 

Aggregate Estimated Value Range Aggregate Cluster Scale Stage Region Opportunity Type $300M – $500M 100 - 160 MW Technical Engagement North America AI Infrastructure Deployment Commercial Negotiation North America AI Infrastructure Deployment Proposal / Design APAC AI Infrastructure Deployment 1,500 - 2,500 GPUs Proposal / Design North America GPU as a Service Deployment Planning APAC GPU as a Service Multi - region enterprise demand Increasing cluster scale Mix of training and inference workloads Mix of GaaS and Al infrastructure deployment 2 4 5 10 15 Deployment Planning Commercial Negotiation Proposal / Design Technical Engagement Opportunities Identified * Qualified pipeline includes opportunities in proposal, negotiation, or deployment planning stages. Active Opportunities 15 Approx. Aggregate AIDC Deployment Size 500 MW Countries Covered 9 Estimated Qualified Pipeline Value $300M AI Infrastructure Pipeline 14 As of April 2026, “Active Opportunities” represents opportunities currently tracked by management in the Company’s internal c omm ercial pipeline. “Estimated Qualified Pipeline Value” represents the approximate aggregate estimated contract value ranges for active opportunities in proposal/design, commercial negotiation or deployment planning stages. Stage counts are cu mul ative and reflect opportunities that have reached at least the indicated stage. “Aggregate AIDC Deployment Size” reflects approximate prospective deployment scale for infrastructure deployment opportunities measured in MW. Pipeline metric s a nd contract value ranges are used by management to monitor commercial activity, are not backlog, bookings or revenue, are non - binding and subject to change or cancellation, and may not result in executed contracts or recognized revenue. Pipeline Overview Selected Active Opportunities (Anonymized) Pipeline Stage Progression (Cumulative) Pipeline Characteristics Certain pipeline opportunities relate to infrastructure offerings that management believes are ready for commercial engagemen t b ut that have not generated revenue to date.

 

 

 

 

Backed by prominent venture investors across multiple rounds since 2022 (1). Selected Financing Milestones 15 November 2025 $500K bridge SAFE financing from Taisu Ventures at a $300M valuation cap. June 2022 Exascale Labs founded. December 2023 $1.485M SAFE financing raised at a $25M valuation cap. December 2024 $7.501M SAFE financing led by Hack VC at a $150M valuation cap. January 2026 Definitive business combination agreement with BCAR at a $500M pre - money equity value. May 2024 $1.65M SAFE financing led by Portal Ventures at an $85M valuation cap. March 2026 $3M SAFE financing raised at a $500M valuation cap. (1) Valuation references reflect transaction valuation caps or reference valuations, where applicable, and are not necessaril y i ndicative of completed priced preferred equity financings.

 

 

 

 

Team 16 Septem Yang Principal Architect M.Eng. in Electronic Engineering, Dublin City University | Ex - Microsoft and Snap Jonathan Jaranilla Business Development Lead Environmental Science, Policy, and Management, UC Berkeley | 15 years of experience in crypto and investment Mark Fidelman Marketing Lead B.A. in Economics, University of San Francisco | Ex - Forbes Hoansoo Lee CEO & CFO Ph.D. in Business Economics, Harvard Business School | Ex - Council of Economic Advisers (Executive Office of the President) Zachary Bright Research & Development Lead Ph.D. in Computer Science, Visiting Scholar at Princeton University | Ex - Ericsson Xander Wu Data Center Ecosystem Lead M.S. in Communication and Information Systems, and M.S. in Management, Stanford | Ex - Bitmain Jas Dhillon Program Manager Master of Science, University of Southern California | Ex - Microsoft, AXON, Ipsos Kelvin Kesse Legal Advisor J.D., Harvard Law School | Ex - Norton Rose Fulbright, and DLA Piper

 

 

 

 

Board of Directors of PubCo 17 Hoansoo Lee CEO & Interim CFO, Director Ph.D. in Business Economics, Harvard Business School | Ex - Council of Economic Advisers (Executive Office of the President) Wenying Jia Chairperson and Director Angel investor | Early investor in Exascale | Experience in digital assets, cloud computing and GPU - based infrastructure Prof. David Card Lead Director & Chair, Nominating and Corporate Governance Committee Ph.D., Economics, Princeton University | 2021 Nobel Laureate in Economics Prof. Shachar Kariv Chair, Compensation Committee Ph.D., Economics, NYU | Chair, Department of Economics, UC Berkeley

 

 

 

 

Market Opportunity

 

 

 

 

Demand is surging, but deployment of AI compute infrastructure is too slow and costly. AI Infrastructure: An Arms Race + Bottleneck 19 (1) Futurum (2) Microsoft (3) Alphabet (4) Amazon (5) Meta (6) OpenAI (7) Turner & Townsend (8) IEA HYPERSCALER AI CAPEX IN 2026 STARGATE PROJECT (6) $6 9 0B+ (1) $500B Combined spend by the four major hyperscalers, up 60%+ from 2025 Meta (5) Amazon (4) Alphabet (3) Microsoft (2) $115B – $135B $200B $175B – $185B $120B+ SoftBank Oracle OpenAI Capital deployment over 4 years, deploying $100B immediately Around 20% of planned data cent er projects could be at risk of delays (7) Only 17 % reported a view that the industry was well prepared (8) MM1

 

 

 

 

Exascale addresses the critical compute bottleneck in the $5.2T AI m arket. AI Compute Demand is Outpacing Infrastructure Supply 20 (unit in gigawatts) 156GW (1) $838B (4) $5.2T (1) AI - related Data Center Capacity AI/GPU Server AI - ready Data Center CapEx (1) McKinsey (2) Bain & Company (3) Introl (4) MarketsAndMarkets Model Size (Parameters) 1.5 billion GPT - 2 1 trillion GPT - 4 3 – 5 trillion GPT - 5 Global Data Center Demand by Workload (1) AI Compute Demand Global Market Size (2030) Compute used for AI training has grown at more than 2x the rate of Moore's Law (2) over the past decade. GPT - 4 alone required 25,000 GPUs running for 90 days (3) to train — and next - gen models are 3 – 5x larger. By 2030, AI workloads will represent 70% of all data center demand (1), up from 53% in 2025. 38.3 40.4 44.9 50.2 56.2 63.5 20.9 31.2 43.7 56.3 71.5 93.3 23.1 31.2 39.5 46.1 52.8 62.2 82.3 102.8 128.1 152.6 180.5 219 2025 2026 2027 2028 2029 2030 AI Training AI Inference Non-AI CAGR: 22%MM1 WK2

 

 

 

 

Appendi xJD1

 

 

 

 

Financial Trajectory and Operating Leverage ($ in thousands) Statement of Operations Highlights Year Ended June 30, Six Months Ended Dec. 31, FY 2025 (Audited) FY 2024 (Audited) H1 FY 202 6 H1 FY 202 5 $7,016 $1,319 $6,807 $2,614 Revenue (5,910) (1,264) (5,735) (2,178) Cost of revenues $1,105 $56 $1,071 $43 5 Gross profit 15.8% 4.2% 15.7% 16.7% Gross margin $(3,045) $(1,846) $(1,597) $(1,816) Loss from operations $(7,660) $(4,956) $(5,285) $(4,641) Net loss (2,892) (1,825) (1,597) (1,764) Adjusted operating loss (1) Operating loss narrowed 12% YoY in H1 FY2026 even as revenue grew 2.6x — gross margin expanded 4.2% → 15.8% YoY (FY24 vs FY25). Revenue Inflection FY2025 revenue was 5.3x of FY2024 revenue. H1 FY2026 revenue ($6.8M) reached ~97% of full FY2025 ($7.0M) in just six months. Gross Margin Expansion Annual gross margin expanded from 4.2% in FY2024 to 15.8% in FY2025, reflecting improved unit economics and operating scale. Operating Leverage H1 FY2026 loss from operations narrowed 12% YoY to $1.6M, while revenue grew 2.6x, demonstrating operating leverage. Source: Exascale Labs Inc. audited annual financial statements. Figures may not foot due to rounding. (1) Adjusted operating loss is a non - GAAP measure, and represents loss from operations excluding share - based compensation expens es. Non - GAAP financial measures have inherent limitations, and should not be considered in isolation or construed as an alternative to los s f rom operations, or as an indicator of Exascale’s operating performance. Adjusted operating loss presented here may not be comparable to similarly titled measures used by other companies. Other companies may calculate similarly titled measures diff ere ntly, limiting their usefulness as comparative measures to Exascale’s data. Exascale encourages you to review its financial information, which will be included in the Registration Statement, in its entirety and not rely on a single financial measure. T he Registration Statement will also contain a reconciliation of Exascale’ s loss from operations to adjusted operating loss. 22

 

 

 

 

The industry is flooded with GPU orders but lacks the infrastructure to turn them into usable compute. The Constraint is Deployment, Not Just Silicon 23 The Power Wall Traditional power distribution fails at >100kW rack densities. 54V architecture is insufficient for MW - scale racks. The Cooling Limit Air cooling is obsolete for next - gen clusters (Blackwell+). Liquid cooling integration remains a massive operational barrier. The “Last Mile” Gap “Finance - first” Neoclouds struggle to commission complex physical sites on time. Chip Delivery (Fast) (Slow) Data Center Delivery & Compute Online The Deployment Gap

 

 

 

 

Exascale Solutions Designed to Address Key AI Infrastructure Deployment Challenges 24 Design, supply chain, and technology constraints can extend deployment timelines Limited Data Center Capacity Delivery, commissioning and integration can extend deployment timelines Complex GPU Cluster Deployment Downtime, underutilization and limited observability can reduce effective compute output Underutilization and Operational Inefficiency Traditional power architectures may become more difficult to scale at very high rack densities Increasing Rack Density Requirements Deployment Challenges Accelerated deployment timelines AI - native Modular Data Center Improved deployment economics Professional & Experienced Deployment Team Improved performance, utilization and reliability Software - defined Monitoring & Optimization Increased power efficiency (2) Smaller footprint (2) Faster install (2) 800V Direct Current Solid State Transformer Exascale Solutions (1) (1) Includes certain infrastructure offerings that management believes are ready for commercial engagement and are not reflec ted in current revenue. Statements on this slide reflect management’s current views regarding selected deployment challenges and the design objectives and potential benefits of the Company’s offerings. Any benefits rela tin g to deployment timing, cost, reliability, performance or efficiency depend on customer configuration, workload profile, site conditions and other assumptions, and actual results may differ materially. (2) Per component vendor specifications.

 

 

 

 

Illustrative positioning across selected AI infrastructure categories Exascale’s Differentiated Approach 25 (1) Reflects management’s assessment as of April 2026 based on publicly available information, third - party industry materials, and management’s understanding of representative market participants. Offerings, positioning, and business models may evolve and may vary by company and over time. (2) The comparison is illustrative and intended to highlight general positioning across selected categories, not to provide a c omplete description of any competitor or category, and should not be interpreted as a ranking or as a statement that any company lacks capabilities not listed. (3) Terms such as ‘selected offerings,’ ‘limited,’ ‘not typical,’ ‘primarily internal use,’ ‘available,’ and similar descrip tor s are qualitative, inherently judgmental, and not based on a uniform industry standard. (4) Exascale’s infrastructure solutions include offerings that management believes are ready for commercial engagement; cert ain such offerings have not generated revenue to date. EXASCALE Solution Providers Neoclouds General Purpose Cloud Yes Limited / not core Yes Limited / Not core AI - Native / Software - Defined Yes Limited Yes Available across general workloads GPU as a Service Yes Customer deployments Primarily internal use Primarily internal use MDC Solutions Yes Selected offerings Not typical Not typical HVDC / SST Solutions Yes Available Primarily internal use Primarily internal use High - Density Liquid Cooling Solutions Yes Limited Internal tools General - purpose tools AI Data Center Management Platforms Asset - light, software - defined modular deployment & operations Hardware / project delivery GPU fleet expansion Owned / leased cloud sites Deployment Model Yes Yes Not typical Not typical Infrastructure Enablement for Third Parties