Execution-Focused Pilot Builds on AZIO AI’s Expanding AI Infrastructure Pipeline and Validates High-Density Power and Cooling Architecture for Next-Generation Deployments

LOS ANGELES, Jan. 15, 2026 /PRNewswire/ — AZIO AI, a next-generation artificial intelligence infrastructure platform, today announced the advancement of a joint immersion-cooled energy infrastructure pilot in collaboration with Envirotech Vehicles (“EVTV”). The execution-focused pilot is designed to validate high-density cooling, power efficiency, and modular deployment frameworks critical to large-scale AI data center expansion.

The initiative builds directly on AZIO AI’s recently announced expansion of its AI infrastructure pipeline, including significant governmental and institutional purchase orders, and reflects the Company’s continued focus on disciplined execution as it advances from contracted demand toward physical deployment.

Infrastructure-Level Validation for High-Density AI Compute

The immersion-cooled pilot is purpose-built to evaluate single-phase liquid immersion cooling systems, modular containerized infrastructure, and integrated power strategies under sustained, high-load operating conditions. The deployment is explicitly focused on infrastructure-level performance rather than application-specific workloads, enabling rigorous assessment of the physical and operational systems that underpin modern AI data centers.

Key validation areas include:

Thermal performance under continuous high-density power loads
Power utilization efficiency and power quality behavior
Cooling system reliability in elevated ambient environments
Hardware lifecycle, serviceability, and maintenance workflows
Modular, repeatable deployment architectures suitable for rapid scaling

The thermal dynamics, power delivery characteristics, and operational insights generated through the pilot are directly applicable to next-generation GPU-driven AI compute environments, where increasing rack densities and power concentration continue to redefine infrastructure requirements.

Pipeline-Driven Infrastructure Execution

As AZIO AI advances from contracted demand toward deployment across its growing project pipeline, infrastructure validation has become a critical priority. The immersion-cooled pilot supports this transition by generating real-world operational data around power density, thermal efficiency, and modular repeatability—key factors influencing deployment timelines, capital efficiency, and long-term operating economics for high-density AI data center environments.

Real-World Operating Environment in Texas

The pilot will be conducted in Texas, a region selected for its combination of high ambient temperatures, industrial-scale energy infrastructure, and continuous-load operating conditions. This environment provides a rigorous real-world testbed for evaluating cooling efficiency, system resilience, and deployment repeatability under conditions representative of many emerging sovereign AI infrastructure markets.

Building Toward Sovereign and Distributed AI Infrastructure

AZIO AI is developing infrastructure frameworks designed to support sovereign AI data center deployments, where local control over data, energy resources, and compute capacity is increasingly strategic. Immersion cooling, modular containerization, and flexible power integration are viewed as foundational technologies enabling:

Rapid deployment of AI infrastructure in energy-adjacent and emerging regions
Energy-aware compute clusters aligned with localized resource availability
Jurisdiction-specific architectures compliant with national data sovereignty requirements

Insights generated through the EVTV collaboration are expected to inform AZIO AI’s design standards, vendor qualification processes, and operational playbooks as the Company scales its global AI infrastructure footprint.

Leadership Commentary

“This pilot is about disciplined execution and real-world validation,” said Chris Young, Chief Executive Officer of AZIO AI. “As our AI infrastructure pipeline continues to expand, validating cooling, power, and modular deployment strategies under sustained operating conditions is essential. The insights generated through this collaboration directly inform how we design scalable, resilient, and sovereign AI data centers globally.”

“As AI workloads continue to drive higher power density and stricter efficiency requirements, infrastructure execution becomes a decisive advantage,” said Elgin Tracy, Chief Operating Officer of EVTV. “This collaboration allows us to apply our experience in power systems and modular deployment alongside AZIO AI’s expanding AI infrastructure pipeline. The focus of this pilot is validating infrastructure models that are technically robust, operationally repeatable, and capable of scaling in step with accelerating AI demand.”

Pilot Scope and Forward Path

The pilot will progress through structured phases, including equipment commissioning, performance benchmarking, continuous operational monitoring, and post-deployment technical assessment. Any expansion beyond the pilot phase will be subject to additional validation, commercial evaluation, and applicable corporate approvals.

About AZIO AI

AZIO AI is an artificial intelligence infrastructure company focused on the design, development, and operation of scalable, energy-efficient AI data centers. The Company emphasizes institutional-grade execution, capital discipline, and modular infrastructure strategies to support accelerating global demand for AI compute, particularly in sovereign and emerging markets.

About EVTV

EVTV is an energy and technology company focused on innovative approaches to power utilization, modular infrastructure, and next-generation deployment models across energy-adjacent sectors.

Forward-Looking Statements

This press release contains certain “forward-looking statements” within the meaning of the United States Private Securities Litigation Reform Act of 1995. These statements include, but are not limited to, statements regarding infrastructure validation, scalability, future deployment frameworks, strategic collaborations, and potential expansion of pilot initiatives. Forward-looking statements are based on current expectations and assumptions and are subject to risks and uncertainties that could cause actual results to differ materially. Readers are cautioned not to place undue reliance on these statements. The Company undertakes no obligation to update any forward-looking statements except as required by law.

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