GDT Opens AI Laboratory at Dallas Headquarters
The new facility provides businesses with a production-grade environment to test generative AI and large language models.
Updated on Oct. 29, 2026 in Data Centers
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GDT has debuted a supercomputer-level AI lab at its Dallas headquarters. The facility allows companies to develop, fine-tune, and compare generative AI models.
Why it matters
The lab serves as a crucial proving ground for businesses attempting to bridge the gap between AI strategy and real-world deployment. By offering hands-on testing, it helps organizations validate their workloads before committing to full-scale implementation.
The lab is powered by a Cisco server featuring eight Nvidia H200 graphics processing units and a 900-pound rack configuration. Network infrastructure includes six Cisco Nexus switches paired with a NetApp all-flash storage system.
The players
GDT
This Dallas-based company provides technology solutions and infrastructure services for global businesses.
Softcat
Based in the United Kingdom, this IT infrastructure and services provider has agreed to acquire GDT for $1.05 billion.
The details
The laboratory setup provides businesses with the necessary compute power to test and compare complex large language models. The integration of high-performance Nvidia hardware and NetApp flash storage allows for high-speed data processing essential for modern AI development.
Timeline
GDT was founded in 1996.
GDT agreed to be acquired by Softcat in September 2026.
The lab held an open house on October 22, 2026.
The acquisition by Softcat is expected to close by the end of Q1 2027.
The Tech Race
The adoption of Nvidia H200 graphics processing units marks a standard industry shift toward higher-density compute for enterprise AI labs. This lab positions GDT at the center of the ongoing arms race to provide businesses with the infrastructure required for generative AI training.
Local businesses gain immediate access to high-end hardware that is otherwise difficult to source or maintain in-house. This facility lowers the barrier to entry for firms looking to integrate advanced language models into their own commercial software or workflows.
The takeaway
Businesses looking to deploy AI should leverage testing labs to identify hardware bottlenecks before scaling operations. This approach minimizes capital risk by confirming the performance of specific models on enterprise-grade infrastructure first.
Further reading
For more on industry infrastructure trends, visit our Data Centers section.
Source note: This article includes information reported by Dallas Innovates.
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Would you use an AI laboratory to test new technologies before purchasing equipment for your business?
