• Modular Solution: BSAI aims to address this shortage by developing modular AI data centers that enable faster deployment and scalable expansion of AI computing capacity. While the market is dominated by larger providers, rapidly growing demand has created opportunities for emerging AI infrastructure companies such as BSAI.
  • Business Model: BSAI plans to develop modular AI data centers across the U.S. and generate recurring revenue by providing on-demand AI computing through its GPU-as-a-Service (GPUaaS) platform. The company is currently pre-revenue and preparing to develop its first facility. A recently announced $62.5M equity financing is expected to fund the initial project. We believe BSAI’s opportunity lies in its ability to execute its strategy and rapidly capture market share, rather than in any proprietary technology or process.
  • CoreWeave Benchmark: CoreWeave (market cap: $46B), the largest publicly traded dedicated AI infrastructure company, highlights the sector's growth potential. Revenue grew from $16M (2022) to $5B (2025), and is projected to reach $13B (2026E). Its unit economics imply ~$4.2M of annual gross profit per MW versus $15M of CAPEX per MW. BSAI plans to develop 200+ MW of AI data center capacity. Applying these unit economics, we estimate BSAI could generate up to ~$1.2B in annual revenue from ~$3B of CAPEX. Based on these estimates, BSAI trades at a 66% discount to forward peer multiples (5x vs 13x revenue; 9x vs 27x EBITDA).
  • Execution-Driven Upside: BSAI is an early-stage, pre-revenue company with significant upside potential if management successfully executes its growth strategy.

Key Risks

  • Early-stage, pre-revenue company - Commercialization and execution of growth strategy
  • Capital requirements – Funding needed to build and scale AI infrastructure
  • Competition – Highly competitive industry dominated by larger players
  • GPU supply – Availability of GPUs and related hardware
  • Permitting – Regulatory approvals and utility interconnections

Price and Volume (1-year)

  YTD 12M
BSAI 25% 53%
OTCQX 15% 27%
DTCR* 38% 58%

* BluSky AI Inc. has paid FRC a fee for research coverage and distribution of reports. See last page for other important disclosures, rating, and risk definitions. All figures in US$.

AI Adoption Across Industries

Artificial intelligence (AI) is being adopted across nearly every major industry to automate processes, improve decision-making, and develop new products and services. As adoption accelerates, demand for high-performance AI computing infrastructure continues to grow.

Organizations requiring AI computing include AI developers (e.g., OpenAI, Anthropic, and xAI), enterprises, startups, research institutions, and governments. Example applications include banks using AI to detect fraudulent transactions and hospitals using AI to analyze medical images and assist physicians with diagnosis.

Source: FRC

Organizations across virtually every industry are adopting AI to improve efficiency and decision-making

The AI Infrastructure Ecosystem

Data centers are the backbone of the AI ecosystem, providing the computing power needed to train and deploy AI models.

Organizations requiring AI computing generally have three options:

  1. Build and operate their own AI infrastructure (e.g., Meta and Google), providing control but requiring significant capital investment and technical expertise.
  2. Rent AI computing from a hyperscale cloud provider (e.g., Amazon AWS, Microsoft Azure, and Google Cloud), which offers AI computing alongside a broad portfolio of cloud services, including storage, databases, and networking.
  3. Rent AI computing from a specialized AI infrastructure provider (e.g., BluSky AI , CoreWeave, Lambda, and Crusoe), whose primary business is delivering high-performance computing infrastructure for AI applications.

Building AI infrastructure requires significant capital, power, and technical expertise, making leased AI computing the preferred option for most organizations, while enabling on-demand scalability

Source: FRC

While hyperscalers dominate the market, specialized providers help meet growing AI demand

While hyperscalers offer AI as one of many cloud services, specialized providers focus exclusively on AI computing, complementing rather than replacing the major cloud platforms. We believe both business models can coexist, much like Amazon coexists with specialized retailers such as and, as the rapidly growing AI computing market is large enough to support both.

Source: FRC

The ability to deliver reliable, scalable, and cost-effective AI computing is often the primary differentiator

Competitive Landscape

The specialized AI infrastructure market remains relatively fragmented, with a mix of established private companies, newly listed public companies, and emerging entrants.

Source: FRC / Various

While most providers operate across North America and Europe, they differ in scale, geographic reach, and stage of development

Source: FRC / Various

CoreWeave (Market Cap: $46B), the largest publicly traded specialized AI infrastructure company, provides a useful case study of the sector's growth potential
Revenue: $16M (2022) → $13B (2026E)
Estimated economics: ~$4.2M in gross profit per MW vs ~$15M in initial CAPEX per MW, implying an attractive payback 
Headquartered in Salt Lake City, Utah

BSAI : Company Overview

While computing demand continues to accelerate, the industry faces constraints related to power availability, high capital requirements, and lengthy construction timelines. BSAI aims to help address this infrastructure gap through its modular SkyMod AI data centers, enabling faster deployment and scalable expansion of computing capacity.

Entered the AI infrastructure business in 2024

Five full-time + four part-time employees 

Redefining AI infrastructure with Modular Data Centers

Source: FRC

BSAI's modular SkyMod platform is designed to deliver AI infrastructure faster, cheaper, and more efficiently than traditional data center developments

Modular AI data centers are increasingly being adopted by specialized AI infrastructure providers. We believe BSAI's opportunity lies in successful execution and capturing a share of the rapidly growing AI infrastructure market, rather than in the uniqueness of its underlying technology or deployment model.

Solutions & Services

The following chart outlines how BSAI plans to deliver computing services.

Source: FRC

Customers can access AI computing resources on demand over the internet through a GPU-as-a-Service (GPUaaS) model

Primary Solutions

BSAI offers three complementary solutions: developing AI infrastructure for organizations building their own AI capabilities, renting AI computing through its GPUaaS platform, and managed infrastructure services, including deployment, monitoring, security, and technical support
We believe GPUaaS will be the primary long-term revenue driver

Target Clients

Source: FRC

BluSky AI targets organizations requiring AI computing infrastructure but lacking the scale, capital, or expertise to build and operate their own AI facilities

Deployment Strategy & Facilities

Source: Company

Illustration of BluSky AI's modular deployment model

Illustrative 4.5 MW SkyMod Design

Modular, scalable designs 

Illustrative 15 MW SkyMod Design

Source: Company

BSAI is targeting 10+ data centers with over 200 MW of planned capacity

For context, the U.S. AI infrastructure market is estimated at 25–35 GW

Source: FRC

SkyMod facilities are designed to move from site selection to operations in months, subject to permitting

Market Overview

Global AI Market Size

Global AI market projected to grow from $391B (2025) to $3.5T (2033), a 31% CAGR

Source: Grandview Research

Global AI data center market expected to expand from $147B (2025) to $811B (2030), a 24% CAGR

Global AI spending forecast to increase from $235B (2024) to $632B (2028), a 29% CAGR
Data center electricity demand is projected to grow 15% p.a. through 2030, over 4x faster than other sectors

Global Data Centre Electricity Consumption

Source: IEA

In summary, we believe the above-mentioned trends provide a favorable backdrop for specialized AI infrastructure providers such as BSAI

Management and Directors

Brief biographies of the company’s management team and board members follow:

Trent D'Ambrosio – Founder, CEO & Director

25+ years of executive leadership across Fortune 500 companies and startups. Background in AI infrastructure, energy, finance, and digital transformation. Former Interim CEO/CFO of Inception Holdings and executive at Montana Power, leading digital infrastructure initiatives. Founded BluSky AI and led its strategic evolution into modular AI infrastructure. B.S. (Business), and MBA.

Founder-CEO currently owns ~80% of the company, though the ongoing and upcoming financings will dilute this stake

Dan Gay – COO & Director

30+ years of leadership in data centers, enterprise IT, telecommunications, cloud, and AI. Former executive at Catapult Solutions, BlockCerts , RackScale , NTI, Montana Power, Qwest, and MCI. Extensive experience in business development, data center development, enterprise sales, M&A, cloud transformation, and commercialization. B.Sc., Arizona State University.

Riley Cooney – Corporate Development & Strategy Officer

~10 years in corporate development, capital markets, M&A, and digital infrastructure. Advised on US$30B+ of infrastructure transactions and 800+ MW of data center deployments. Expertise in financing, investor relations, and growth strategy.

Three out of five directors are independent 

Andrea Huels – Chief AI & Growth Officer

18+ years in enterprise AI, commercialization, and go-to-market strategy. Former AI executive at Lenovo and Vody. Named among the "50 Most Powerful Women in Technology"; speaker at NVIDIA GTC, IBM Think, and Yotta. Expertise in AI strategy, partnerships, and enterprise adoption.

Jules Bedard - Chief Technical Officer

15+ years leading IT security teams, specializing in automation, AI, and information security. Developed the first Bitcoin escrow service and anti-fraud service. Developed AI applications for a SaaS company and a proprietary LLM for an AdTech company. CDI College, Canada, Networking, Development, Security.

We believe management's expertise aligns closely with BSAI's business strategy, spanning digital infrastructure, data centers, cloud computing, and capital markets

Rodney Sperry - Chief Financial Officer

18+ years leading accounting services firms serving in manufacturing, distribution, mining, and energy. Served as an outside controller for 14 years for public companies responsible for SEC filings and compliance.

Theodore P. Botts – Independent Director

40+ years of experience in investment banking, corporate finance, capital markets, M&A, and corporate governance. Former executive at Chemical Bank, Goldman Sachs, and UBS. President of Kensington Gate Capital since 2001 and Chair of the Audit Committee at Remark Holdings. Appointed to BluSky AI's Board in May 2026. 

Whit Cluff –  Independent Director

35+ years in commercial real estate, land development, mixed-use, industrial properties, and asset management. Extensive public and private company experience in site selection, infrastructure planning, negotiations, and project execution. U.S. Army veteran.

Mort Aaronson – Independent Director

35+ years of executive leadership experience. Former senior executive at MCI, CEO of KN Energy, Enable, and Ricochet Networks, and founder of three adtech companies. Currently advises Fortune 500 CEOs through Marshall Goldsmith's 100 Coaches.

Financials

Source: FRC / Company

At the end of Q1-2026, the company had $0.56M in cash, ($2.65M) in working capital deficit, and no debt
Subsequent to quarter-end, BSAI launched a $62.5M equity offering 

Comparables Valuation

* BSAI's EV/Revenue and EV/EBITDA multiples are based on our projected revenue and EBITDA at 200 MW of installed capacity.

Source: FRC / S&P Capital IQ

BSAI trades at a 66% average discount to forward multiples (5x vs 13x revenue; 9x vs 27x EBITDA)
Applying sector average multiples to our estimates implies fair values of $15.65/share based on revenue, and $18.56/share based on EBITDA
Given BSAI's early-stage status relative to larger, more established peers, we apply a 90% discount for conservatism

FRC Projections and Valuation 

We assume the SkyMod infrastructure has a useful life of approximately 25 years, while GPUs and AI servers are replaced every five years, consistent with industry practice. Accordingly, our model assumes annual maintenance CAPEX of 10% of initial CAPEX to reflect ongoing GPU refreshes and infrastructure maintenance.

Source: FRC

Our DCF valuation is $15.35/share, based on BSAI reaching 200 MW of installed capacity by 2030
Our assumptions for unit revenue, gross profit, initial and maintenance CAPEX, and capital structure are broadly in line with comparable companies

We are initiating coverage with a BUY rating and a fair value estimate of $15.81/share, based on the average of our three valuation methodologies. BSAI offers investors exposure to one of the fastest-growing technology markets, with significant upside if management successfully executes its 200+ MW AI infrastructure strategy. While execution, financing, and commercialization risks remain high, we believe the current valuation does not fully reflect the company's growth potential.

Risks

We believe the company is exposed to the following key risks (not exhaustive):

  • Early-stage, pre-revenue company
  • Execution – Business model has yet to be proven at commercial scale
  • Capital requirements – Significant funding will be required to deploy and scale the company's planned AI infrastructure
  • Competition – Highly competitive industry dominated by larger players
  • GPU supply – Availability and timely delivery of GPUs and related hardware.
  • Permitting:  AI data centers require multiple permits and approvals, including zoning, environmental, building, and, where applicable, power interconnection approvals. Delays in permitting or power availability could increase costs and delay commercial operations.
We are assigning a risk rating of 4 (Speculative)