AI Infrastructure, Systems & Models

Needham’s AI Infrastructure, Systems & Models coverage spans the full technology stack behind how AI is built, powered and run. The practice covers the dedicated silicon, systems and software that enable AI workloads, the AI factories that supply compute at scale, and the models themselves.

In silicon and systems, Needham focuses on AI accelerators and dedicated silicon (GPUs, ASICs, FPGAs and custom AI chips); high-speed interconnect and AI networking, spanning networking silicon, silicon photonics and co-packaged optics; memory systems spanning high-bandwidth memory (HBM), memory processing units (MPUs) and scale-up memory fabrics; advanced packaging; and the server, rack and AI factory architectures – including neocloud and AI cloud platforms – that deliver compute across large-scale AI data centers and high-performance computing (HPC). In infrastructure software, Needham focuses on AI platform and systems software spanning data pipelines and infrastructure, training and inference optimization, orchestration and MLOps, model serving and developer tooling. In models and platforms, Needham focuses on foundation models, LLMs and the generative and agentic AI platforms built to serve them.