Good morning, everyone. Q3 2025 was a transformational quarter for DigiPower X, as we strengthened our balance sheet, accelerated our shift into AI infrastructure, and delivered positive net earnings.

Quarter highlights: working capital went from half a million dollars in Q3 2024 up to $15 million this quarter; net income positive $300,000 versus a $6.4 million loss last year; EBITDA $1.9 million positive; adjusted EBITDA $0.8 million positive; digital assets: BTC holdings up 143% to 97 Bitcoin, Ethereum 1,000 tokens, total digital currency value $15.4 million, up 213% year over year; warrants reduced from 8.8 million warrants to 2.6 million outstanding; debt: no long-term debt; CapEx: $3.1 million in Q3, $9.5 million year to date, primarily tied to Tier 3 AI data center conversion. Strategic and operational progress: our first ARMS 200 Tier 3 AI pod assembly began in Q4 2025 and will be online in Q1 2026; approved 60 MW load study in New York, enabling future AI expansions; first NVIDIA B200 cluster built with Supermicro on track for Q1 2026 activation; advancing long-term colocation and AI compute agreement with multiple potential customers; beginning January 2026, ARMS 200 modules will be deployed across all Tier 3 sites; energy revenue grew 112% year over year to $8.7 million; cost of revenue and depreciation reduced by $9.3 million year to date; NeoKlaudZ, our GPU-as-a-service platform launching January 2026.

Financial position today: over $90 million in cash, BTC, ETH, and equivalents, the strongest liquidity in company history; our liquidity equals more than one-third of our market cap; this capital fully supports the 2026 AI infrastructure build-out. AI transition across power assets: Phase 1 deployment: Q1 2026 5 MW; Phase 2: Q2 2026 15 MW; Phase 3: Q3 2026 an additional 30 MW; so by Q4 2026, we will have deployed 55 MW, which is 40 MW critical IT load.

Current power availability: Alabama 55 MW, New York Upstate 141.7 MW, for a total of close to 200 MW of power available for 2026; North Carolina an additional 200 MW anticipated in 2028. DigiPower X is now firmly positioned as the next-generation Tier 3 AI infrastructure company.

With the ARMS 200 platform, the NeoKlaudZ platform, major power capacity, and Tier 3 deployment under way, we are building a scalable, high-density AI compute ecosystem ready to serve both emerging AI companies and enterprise customers. We've never been better positioned for growth.

great question, Jeremy. Related to the scaling up of our first module infrastructure ARMS 200 in Alabama, which we intend to complete quarter after quarter up to 40 MW of IT load, mostly 75% to 80% will be colocation.

The colocation range is about $140 to $150 a kilowatt-hour per month to give you a little bit of a size of income. If we average 20 MW because we're scaling up, we estimate roughly about $50 million in revenues average for the year 2026 in colocation.

The second part of AI revenues will be our GPU-as-service through our NeoKlaudZ platform, which we built with Supermicro. That, we anticipate about 1,024 B200, B300 NVIDIA chips, GPUs online generating with a scale-up about $15 million.

The gross estimate for 2026 related to the execution of the infrastructure through our ARMS 200 system solution should be roughly about $65 million. On top of that, we will have the existing Bitcoin mining, which should be even with last year.

We have to add a fourth stream of income, which is our energy sales to the grid through our power plant, which to give you a sense for this year so far, we are at $8.9 million year to date selling energy, which is for Q3 was about $3.1 million energy sales, which will represent on this quarter Q3 over 35% of our revenues. So...

We do not hold any long-term debts. We are current.

We have no obligations, no trigger that could hurt the company. We are completely debt-free.

I think we have the lowest payable ever in our company.

We are holding a little bit more than $90 million total. Most of it is in cash.

We have few holding of crypto Bitcoin mining, about 115 or 16 Bitcoins, and we have 1,000 Ethereum. Everything else is in cash.

That accounts today a little bit above $90 million, which allow us to really develop our modular system. We actually this year, year to date, already spend close to $10 million.

The first development of Q1 are already been paid for. The first ARMS 200, which will be assembled in the next few weeks in Alabama, and that's Rated 3, will be on end of December, tested the first week of January along with Supermicro team, as we plan to have this ARMS 200 system on the partnership book of Supermicro.

Which will be a very interesting development for us.

Right, DigiPower X wholly owned subsidiary US Data Centers, Inc. has developed a proprietary ARMS platform, ARMS for AI-Ready Modular System.

We developed that platform early this year, I would say 10, 11 months ago with Supermicro, and it's really an incredible product system that we can also developed for our own sites and for other people's sites. We can deliver this system within 180 days, and it's built for all kind of chips, primarily for the NVIDIA B200, B300.

It can be customized for other servers or other chips. It's really a modular system that has three product line: 1 MW, 5 MW, and 10 MW.

We can expand it much faster than an hyperscale building that takes a couple of years. In our opinion, for 2026, this is an incredible demonstration of what we can do at the speed we can do.

Of course, the reason why we can develop it in a faster way than an hyperscale is that we already have the high-voltage substations, we already have the connection with the grid power, our power plant generate power as well, we're connected already with power. All we need to do is to insert this modular system that are Rated 3, ready for redundancy and uptime in compliance with the Tier 3.

I think you're allowed to 1.6 hour of downtime a year. We are ready.

We got Rated 3. 2026 gonna be a real transformational year for us, and we expect to enter a full cycle of developing AI.

We developed a very interesting relationship with Supermicro. They're a pretty large company, they have a very good relationship with NVIDIA.

In order to leverage their human resources and resources, we choose Supermicro. We integrated their optimized servers rack directly to our ARMS system pods, and we designed it that way.

Supermicro is doing a very big part of the job by supplying racks ready to go. We also partner with them on all the software integration, and it's really very, very helpful that allows us to have a very big team on our side with a very small G&A, because we're a very low SG&A, and we are leveraging the Supermicro team.

They are coming to our site actually end of this month, November 28th. They will come and start to prep with our people the setup of our modular systems both in upstate and in Alabama.

We developed that platform. Actually, Alec Amar developed it along with, again, Supermicro.

It's geared for the smaller players, not for the hyperscaler customers. It's for the AI developers or ML engineers, start-up companies.

There's plenty of start-up companies now that need access to a infrastructure, and it's hard for them to get access to an hyperscaler. Research institutions and universities, non-hyperscaler corporation priced out of AWS, Azure, or NVIDIA cloud capacity, HPC workloads for simulation, modeling, and data processing.

We will serve it's kind of our retail service, GPU-as-a-service. We expect to develop that portal of a direct vertical GPU-as-a-service to be 20%, 25% of our total revenue.

The breakdown would be 75% colocation with longer contracts, and we are in negotiation now anywhere from 5 to 10 to 15-year contracts. There's a lot of demand for 2026, early 2027.

We are trying to get the best scenario or the most solid contract, 15-year contract, it's like a modified lease on AI infrastructure. Simultaneously, we are developing this it's ready, will be online January we're developing this platform, NeoKlaudZ, backed by Supermicro.

We will be able to integrate multiple customers, all kind of customers, for deep learning, for any kind of applications. That will result in a much higher margin.

The colocation margins are pretty set and revenues. The direct GPU-as-a-service provide very high margin.

Blended, we will have a very healthy margin in the AI business.