Predictive Oncology Q2 Earnings Call Highlights

Axe Compute reported its first full quarter of compute revenue in the second quarter of 2026, while outlining a larger pipeline of contracted AI infrastructure projects that management expects to deploy over the coming quarters.

The company said second-quarter revenue totaled $3.2 million, compared with $35,000 in the first quarter. Chief Financial Officer Jeremy Yaukey-Witter said all compute revenue during the period came from Axe Compute’s Access business, which provides customers with access to GPU capacity. Revenue from its Build business, under which the company designs, deploys, owns and operates dedicated GPU clusters, has not yet begun.

“Build revenue has not yet started. That begins at go live,” Yaukey-Witter said during the company’s earnings call, which was held from a Columbus, Georgia, data center where Axe Compute is preparing to launch an NVIDIA B300 cluster.

Contracted backlog and deployment plans

Chief Executive Officer Christopher Miglino said Axe Compute had signed more than $3 billion in contracts and expects annualized run rate to exceed $696 million when its signed projects are fully deployed. The company defines annualized run rate as annualized monthly recurring revenue upon full deployment of signed contracts, rather than revenue recognized under GAAP in a given reporting period.

Through the end of the second quarter, Axe Compute had signed $317 million in total contract value, including a $260 million contract announced in April. In the first six weeks of the third quarter, the company added $2.9 billion through three Build contracts announced in July, Yaukey-Witter said. That brought year-to-date total contract value through August to more than $3.2 billion.

Axe Compute exited the second quarter with a $37 million annualized run rate, according to management. The company expects that figure to rise to about $139 million as its April cluster enters service in the third quarter, including continued growth in Access. The full signed contract base is expected to be deployed from the fourth quarter through the first quarter of next year, management said.

Miglino said the Columbus cluster is nearing launch and could contribute roughly $20 million to $21 million of quarterly revenue once live. The company also plans to expand the facility’s cluster to three times its current size, using a contiguous network architecture.

Prepayments and financing approach

Axe Compute announced that it had received an initial customer prepayment of more than $317 million for an expanding cluster. Miglino said customer down payments generally range from 20% to 45% of project costs, and the company seeks project financing backed by the revenue streams associated with its customer contracts.

Management said its goal is to use customer prepayments and project-level financing to fund deployments, rather than raising capital at the corporate level. Miglino said the company could invest equity in projects if it considers the timing appropriate, but characterized project financing as its preferred approach.

The company also announced an agreement for an additional 55 megawatts of capacity across multiple locations with Duos Technologies. Duos Chief Executive Officer Doug Recker said the company uses a modular approach to data-center construction, including prefabricated electrical and cooling components that can be installed as capacity is added.

Miglino said Axe Compute and Duos also plan to participate in ownership of certain data-center projects through special-purpose vehicles. He said the structure is intended to provide capital for new facilities where power and other infrastructure are available.

Quarterly loss reflects digital asset valuation changes

Axe Compute reported a second-quarter net loss of $17.2 million. Yaukey-Witter said the result included $13.1 million in losses on digital assets, primarily unrealized fair-value changes in the company’s Ether holdings.

The company introduced adjusted EBITDA as a performance metric during the quarter. Adjusted EBITDA excludes interest, taxes, depreciation, amortization, stock-based compensation and unrealized fair-value changes in digital assets, among other items. On that basis, Axe Compute reported adjusted EBITDA of approximately negative $4.9 million for the quarter. About $900,000 of that amount was related to its legacy drug-discovery service segment, Yaukey-Witter said.

For the first half of 2026, the company generated $17.4 million in positive operating cash flow, driven primarily by customer prepayments. Customer prepayments totaled $60.8 million as of June 30. Axe Compute ended the quarter with $21.9 million in cash, up from $6.9 million at the end of the first quarter.

Contract liabilities included $33.6 million expected to be recognized as revenue within 12 months and $27.1 million in long-term contract liabilities as of June 30. These balances represent customer prepayments connected to executed compute contracts, the company said.

Pipeline and hiring plans

President Kyle Okamoto said Axe Compute was tracking $5.9 billion in active qualified pipeline across 98 open opportunities as of August. Roughly two-thirds of that pipeline by dollar value involves demand for NVIDIA Blackwell-class GPUs or Vera Rubin systems, he said.

The company is adding more than 20 employees in deployment, operations, infrastructure engineering, customer support and commercial operations. Okamoto said each planned hire is supported by signed contracts, rather than anticipated demand.

Looking ahead, management set an objective of securing an additional $2 billion in signed contracts by the end of 2026. Miglino said the company’s priorities are to continue adding agreements while building the operational infrastructure needed to deploy and manage AI clusters globally.

About Predictive Oncology (NASDAQ:POAI)

Predictive Oncology, Inc is a biotechnology company that leverages artificial intelligence and digital biology to support drug discovery and development in oncology. Its core business revolves around the application of machine learning algorithms to high-content cellular imaging, multi-omic profiling, and clinical response data. By integrating these diverse data streams, the company aims to generate predictive models that forecast the efficacy and toxicity of candidate therapeutics, thereby accelerating preclinical decision-making and reducing development timelines.

The company’s primary offerings include its Phenomics platform, which combines automated microscopy with advanced image analysis to capture subtle phenotypic changes in cancer cells.