WAYNE, PA — Cornelis is expanding its distribution and federal integration partnerships as demand grows for high-performance networking infrastructure capable of supporting large-scale artificial intelligence and high-performance computing workloads.
The company said new channel relationships with ASI Corp., CTG Federal, and TVAR Solutions will expand access to its CN5000 networking platform across enterprise, academic, and government markets.
The expansion comes as AI infrastructure operators face increasing pressure to improve computing performance while managing power consumption, hardware costs, and deployment timelines tied to large-scale data processing environments.
Cornelis stated its CN5000 platform provides 400-gigabit networking designed to reduce latency and improve cluster efficiency in distributed computing environments.
The company claims the platform delivers lower latency, higher message throughput, and improved scaling efficiency compared with competing 400G networking fabrics, allowing organizations to complete AI and HPC workloads with fewer compute resources.
“Customers are under increasing pressure to deliver more compute within fixed power, space, and budget constraints, and they can’t afford inefficient architectures that leave performance stranded,” Chief Executive Officer Lisa Spelman said in a statement.
Federal systems integrators involved in the expansion pointed to growing government demand for AI and HPC infrastructure that can be deployed quickly and reliably.
“Federal agencies aren’t asking for networking experiments, they’re asking for proven technology that ships on time and runs well,” CTG Federal Chief Technology Officer Brad Baker said in a statement.
Cornelis said the expanded partner network will support deployments across research universities, defense agencies, manufacturing, energy, life sciences, and financial services organizations.
The company also noted that channel partners will receive joint sales support, technical training, and access to validated infrastructure architectures intended to accelerate deployment of AI and HPC systems.
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