Keysight Technologies, Inc. (NYSE: KEYS) introduces the Keysight Artificial Intelligence (KAI) architecture, a portfolio of end-to-end solutions designed to help customers scale artificial intelligence (AI) processing capacity in data centers by validating AI cluster components using real-world AI workload emulation. Providing system-level interoperability, performance, and efficiency insights, KAI helps operators maximize system performance and pinpoint performance issues not found when testing individual components.
Scaling AI data centers requires testing throughout the design and build process — every chip, cable, interconnect, switch, server, and graphics processing unit (GPU) needs to be validated at both the component and system level. Full-stack workload emulation complements physical layer testing, revealing insights not found when testing components alone. Customers can extract peak AI performance sooner, increasing capacity more quickly and maximizing the return on the billions spent on AI clusters.
The KAI architecture enables AI providers, semiconductor fabricators, and network equipment manufacturers to:
- Accelerate design: Debug cutting-edge high-speed digital designs; meet or exceed the latest PCIe, DDR, and CXL standards.
- Accelerate development: Verify component-level compliance, including high-speed interconnects, cables, and chipsets, and validate workload performance at the system level.
- Accelerate deployment and operations: Validate and tune system-level performance across the entire data center, reducing the risk of workload failures by using end-to-end emulation to pinpoint system performance issues before deploying in production.
The Keysight AI architecture, which includes the newly announced KAI Data Center Builder, features four portfolio suites that together address all aspects of AI data center design, from pre-silicon simulation through post-deployment system testing and troubleshooting.
- KAI Data Center Builder. Emulate high-scale AI workloads with measurable fidelity to improve system performance, predict and mitigate the impact of component failures, and optimize data center operations.
- KAI Compute. Optimize high-speed digital designs and pioneer next-generation AI chip development with a suite of AI-ready tools that includes electronic design automation, bit-error ratio testers, oscilloscopes, and arbitrary waveform generators.
- KAI Interconnect. Validate optical and electrical data paths to ensure scalable, high-speed connectivity up to 1.6T with a suite of AI-ready tools, including sampling oscilloscopes, photonic power meters, and network interconnect testers.
- KAI Network. Benchmark AI network performance, detect bottlenecks, and optimize AI workload distribution with a suite of AI-ready tools that includes AI workload emulators, distributed network traffic generators, and network traffic emulators.
- KAI Power. Optimize power efficiency and energy management across data center components with a suite of AI-ready tools that include oscilloscopes, power rail probes, and electronic design automation.
Alan Weckel, Founder and Technology Analyst, 650 Group, said: “Accelerating design and deployment of next-generation AI/ML ASICs is key to unlocking the market as customers move from foundational training to agentic models. AI interconnect through scale-up, scale-out, and frontend networks will drive record 800GE and 1.6T port shipments over the next several years with one of the fastest innovation cycles to ever occur in the industry. The Keysight Artificial Intelligence architecture and KAI Data Center Builder solution will help customers scale and adapt to this new market opportunity.”
Ram Periakaruppan, Vice President and General Manager, Network Test & Security Solutions, Keysight, said: “Scaling AI data centers requires more than component-level validation. Interoperability, performance, and efficiency are system-wide metrics that can only be measured under real-world network conditions. Keysight’s AI solutions integrate our deep experience in traffic emulation, component, and network compliance validation, and the latest industry standards to emulate every aspect of data center performance: compute, network, interconnect, and power to ensure AI infrastructure meets evolving demands.”
