Data Leaf AI Inc.

Data Leaf builds decentralized, modular AI data centers with renewable energy, creating scalable, energy-efficient AI compute.

We have a pipeline of over 30 projects with 5 projects at stages that are capable of 2025 ITC credits and Q1 2026 revenues.
We are currently registering a couple of our projects for ITC bonuses.
In addition, we are in discussions to provide one of our vendors with up to 200 units of our modular data centers over the next 12 to 14 months with terms that allow for cash flow positive production.
The team has decades of IT, Data, Communications and Renewable experience and multiple start ups as founders.

Data Leaf AI is a B2B business model with demographic target markets of businesses requiring AI and Large Language Model compute power within the "Sub-5MW, Geographically Distributed Segment". While current projects are in California, the target market is global. This global market for AI compute and colocation (TAM) is currently valued at $500 billion, with the company's serviceable market (SAM) valued at $60 billion. The market is rising rapidly, with a projected 25% compound annual growth rate in Data Leaf's target segment from 2025 to 2034, and the total market is forecasted to reach $2.39 trillion by 2034. The provided document quantifies the market in monetary value but does not specify the number of hypothetical customers.

The rapid growth of artificial intelligence is creating a massive demand for new energy and data infrastructure that current systems cannot support. The vast majority of new energy interconnection requests fail, with over 70% being withdrawn, creating a critical bottleneck. This failure to build adequate infrastructure presents significant risks, including economic stagnation, compromised national security, and a loss of technological leadership. The situation necessitates innovative and efficient solutions to prevent an impending AI infrastructure crisis.

By drawing on a decade worth of small PV projects that could not attain an interconnection, we have compiled projects that can bring our modular Data centers online and with revenues in 12 to 14 months. We have 2 projects that can be online with revenues between end of 2025 and Q1 2026 with an additional 3 projects being safe harbored for 2025 ITC.

Data Leaf AI is specifically focused on using large numbers of partially developed projects that ultimately failed the interconnect study (70%+ of all PV projects developed) but were otherwise great projects for Solar, to fill our pipeline and bring projects together that use ag zoning and relatively simple permitting with neg dec Environmental Impact Studies to be able to rapidly deploy at scale.
While the specific model to address the problem with access to power is unique, the competition for revenue share cannot be dismissed.

Our key competitors; Crusoe Energy Systems, Applied Digital, CoreWeave

Crusoe Energy Systems: Crusoe remains the most direct competitor, particularly concerning the monetization of underutilized energy.

Strengths: Crusoe's entire business model is a variation of BaaS™, converting wasted energy into revenue. Their "Digital Flare Mitigation" and "Digital Renewable Optimization" services are market-leading examples of opportunistic compute. Their modular deployment is fast and efficient.

Weaknesses: Crusoe's primary model tethers them to specific geographic locations (oil wells, renewable farms), potentially limiting their flexibility compared to Data Leaf's broader site selection criteria. Critically, their model is designed for off-grid, behind-the-meter power use, making them less likely to compete in grid services and sales.

Data Leaf's Edge: Data Leaf's planned ability to pursue an interconnection and sell power to the grid or other offtakers is a significant differentiator. This provides an additional, potentially more stable, revenue stream that Crusoe's current model does not address.

Applied Digital: Applied Digital focuses on massive scale, which presents a different kind of challenge.

Strengths: The company excels at developing very large (multi-hundred-megawatt) data center campuses in low-cost energy regions. Their history in cryptocurrency mining shows experience in opportunistic compute.

Weaknesses: Their "speed to market" is for massive, long-term projects. The timeline to bring a 100MW+ facility online is significantly longer than Data Leaf's stated 12-14 months for a smaller, more agile deployment. They do not appear to have a strategy for grid sales or balancing services.

Data Leaf's Edge: Data Leaf's superior agility and comprehensive speed-to-market for 1-5MW facilities is a major advantage for clients who cannot wait for large campus build-outs. The ability to deploy to existing operational sites within weeks of a contract is a capability that large-scale builders like Applied Digital cannot easily match.

CoreWeave: A high-growth AI cloud provider, CoreWeave is more of a strategic partner or a potential large-scale customer than a direct competitor on the infrastructure and energy-services front.

Strengths: CoreWeave provides best-in-class, on-demand access to the latest NVIDIA GPUs, making them a leader in the AI cloud market. Their rapid expansion gives them a significant global presence.

Weaknesses: As a lessee of data center space (from companies like Applied Digital), CoreWeave has little control over the underlying power infrastructure. Their business model is not focused on energy generation, BaaS™, or grid services. They are a consumer, not a producer, of these capabilities.

Data Leaf's Edge: Data Leaf is an infrastructure provider, a fundamentally different business model. While a company could choose CoreWeave's cloud over building its own data center, Data Leaf's offering is for entities seeking dedicated, owned, or leased infrastructure with specific operational and energy advantages, including the future potential for revenue from power sales.

Financial Model & Key Indicators
The company's Primary Channel financial model is based on developing portfolios of 10 projects at a time. The key financial indicators for a single 10-project portfolio are as follows:
Capital Expenditures (CapEx): The total cost for one portfolio is approximately $147.0M, broken down into:
AI Compute and BaaS™: $55M (37.4%)
Battery Storage: $30M-$48M (26.5%)
Solar System: $33M (22.4%)
Data Centers: $20M (13.6%)
Projected Annual Revenue Streams (per portfolio):
AI Compute Base Load: $50M+ per year
Crypto Mining (from excess energy): $10M+ per year
LCFS & REC Credits: $1.2M

5-Year Sales Expectations
Data Leaf has strong expectations for revenue growth over the next five years, driven by sales from its Modular Data Center (ModDC) and AI Compute offerings. The total projected non-EBITDA revenues are as follows:

Year 1: $25.9M (sum of $14.6M from ModDC and $11.3M from AI Compute)
Year 2: $141.5M (sum of $82.5M from ModDC and $59.0M from AI Compute)
Year 3: $240.4M (sum of ModDC and AI Compute)
Year 4: $378.1M
Year 5: $551.1M

The company's stated 5-year goal is to develop 10 portfolios, representing 100MW of AI Compute, with a target valuation of

Data Leaf AI Inc. operates through three distinct channels.
Our core business, Channel 1 SSD, serves B2B clients with a flexible pricing model based on GPU/hr, CPU/hr usage. Using our BaaS™ system, we leverage excess renewable power for opportunistic crypto mining and to support Web3 initiatives. Channel 2 focuses on selling our adaptable modular data center designs, which are optimized to work with a partner's patented cabinet technology.
Channel 3 accelerates hyperscale development by enabling strategic partnerships with larger data center developers.

The focus will be on getting our first two SSD Projects (Oasis and Jaworszek) into revenue revenue stage and securing safe harbor for the next 2 projects. Below is a breakdown of spend;

Complete Due Diligence and secure site control for additional 8 projects to complete the portfolio (30%):

Equipment (45%): Down payments on PV system, Storage, Compute. (30/70 split of equity to debt) (Down payments on 2 additional projects will secure Safe Harbor ITC positions as 2025 Projects.)

Engineering & Permitting (15%): Finalize all pre-construction requirements.

Team & Operations (10%): Expand our core team to manage execution.

We are looking to raise $10M as part of our series A. We recognize the value of a capital driven market and feel that the market is the best way to provide a valuation and equity model.

While Data Leaf Inc. presents a strong model, several risks could impede its success, stemming fr om competition, potential crises, and technological shifts.

Execution and Financial Risks: The business model is highly capital-intensive, with each 10-project portfolio requiring $138M-$156M in investment. A financial crisis or tightening credit markets could make it difficult to raise the necessary "$110M Debt" and "$10M Equity" for each portfolio, stalling growth. Operationally, the business is complex, integrating solar, battery storage, and data centers. Any failure or delay in the difficult California permitting process, wh ere all initial projects are located, could jeopardize timelines and revenues.

Market and Competitive Risks: The company's revenue relies heavily on a continued, high-growth market for AI compute and the volatile price of crypto, which is used to monetize excess energy. A slowdown in AI demand or a crash in crypto value could severely impact profitability. Furthermore, the competitive landscape includes formidable players:

Crusoe Energy Systems directly competes by monetizing stranded energy for compute with very low operating costs.

Applied Digital focuses on large campus build-outs, which may be more attractive to larger clients, and has a history of adapting to market changes like crypto mining.

CoreWeave is a capital-light competitor that leases its infrastructure, allowing it to scale its cloud services rapidly without owning the underlying assets.

Technological and Regulatory Risks: The business model's viability is tied to current technology. A breakthrough in AI chip efficiency that drastically reduces power consumption could devalue the company's core offering of integrated power and compute. Similarly, new, cheaper battery storage technologies could render their planned BESS investments obsolete. On the regulatory side, a change in rules for LCFS & REC credits could eliminate a key revenue stream, and a shift in California's energy or permitting laws could create insurmountable hurdles for their geographically concentrated projects.

Finally, the loss of or phasing out of the ITC will affect a very valuable component in the financing of the PV and BESS systems.

Upward Labs in 2022/23
While Data Leaf has not participated as a company with an Incubation or Accelerator, Scott Lane, during his time as CoFounder and COO at EarthGrid PBS participated in Upward Lab's Accelerator Program.

While not the presenter or with Data Leaf, Scott Lane participated in and accepted several rewards alongside of Troy Helming, including Pepperdines "Most Fundable."

Trademarks
IP includes processes
Patent for Mod DC is still in discussion.