Lenovo AI Express Accelerates the Path to Production-Ready Hybrid AI
Lenovo has introduced Lenovo AI Express, a new accelerated approach designed to help organizations move AI projects from experimentation into production more quickly. Developed in collaboration with NVIDIA, the offering combines validated AI infrastructure, accelerated computing, software and services to simplify the process of deploying and scaling enterprise AI.
As businesses move beyond AI pilots and begin deploying AI applications at scale, infrastructure requirements can become increasingly complex. Organizations need the right combination of compute capacity, networking, software, data protection and support — without overbuilding infrastructure before demand is fully understood.
Lenovo AI Express is designed to address this challenge by providing pre-validated, right-sized configurations that can be deployed quickly and expanded as requirements grow.
According to Lenovo’s 2026 CIO Playbook, organizations moving from AI experimentation to scaled execution expect an average return of $2.79 for every $1 invested, while 93% of enterprise respondents anticipate positive returns from their AI investments. However, long procurement cycles, integration challenges and infrastructure readiness can delay the transition from investment to business value.
Lenovo AI Express aims to shorten that path.
For eligible configurations, order-to-ship times can begin at 15 business days, allowing customers to start with infrastructure sized for their current workloads and budgets before scaling as AI models, users, data volumes and inference requirements increase.
“Organizations are navigating today’s complexity and constraints to get AI into production faster, looking for an approach that fits their current needs while giving them the ability to scale as those needs evolve,” said Ashley Gorakhpurwalla, President, Infrastructure Solutions Group, Lenovo. “Lenovo AI Express gives our customers an accelerated path to deploying AI infrastructure to fit their specifications while mitigating the risk of overbuilding or costly delays.”
Start faster and scale with confidence
Lenovo AI Express provides a streamlined route to the Lenovo Hybrid AI Factory with NVIDIA, combining Lenovo infrastructure with NVIDIA accelerated computing and AI technologies.
Rather than requiring organizations to design an AI environment from the ground up, customers can choose from three validated configurations based on their expected model sizes, number of users and throughput requirements.
Small: From 15 Days
The Small configuration is designed for focused AI inference workloads supporting tens of users at more than 30 transactions per second (TPS). It supports average model sizes ranging from 7 billion to 70 billion parameters.
The configuration is built on the Lenovo ThinkSystem SR650a V4 and powered by two NVIDIA RTX 6000 PRO Blackwell Server Edition GPUs, providing a starting point for organizations looking to bring targeted AI applications into production.
Medium: From 20 Days
The Medium configuration is designed for higher-throughput inference and agentic AI workloads supporting hundreds of users at more than 30 TPS.
It accommodates average model sizes from 70 billion to 400 billion parameters and is built on the Lenovo ThinkSystem SR675 V3, powered by eight NVIDIA RTX 6000 PRO Blackwell Server Edition GPUs.
This configuration is aimed at organizations moving beyond individual AI applications toward broader enterprise deployments and more demanding workloads.
Large: From 25 Days
The Large configuration is designed for enterprise-scale generative AI deployments serving thousands of users across a broad range of workloads and interaction levels.
Supporting models of up to one trillion parameters, the configuration is built on the Lenovo ThinkSystem SR680a V4 and powered by NVIDIA HGX B300.
This provides organizations with a foundation for large-scale AI environments where compute requirements, user demand and model complexity can be significantly higher.
Across all three configurations, Lenovo AI Express also supports the latest CPU technologies from AMD and Intel, giving organizations additional flexibility when selecting infrastructure based on their workload requirements.
Customers can further customize their environments with enterprise AI software, including Red Hat AI Factory with NVIDIA or NVIDIA AI Enterprise. For organizations seeking additional protection for AI applications, data, models and pipelines, Veeam Kasten can also be included.
Simplifying the AI infrastructure journey
Infrastructure is only one part of bringing AI into production. Organizations also need to identify valuable use cases, validate expected returns, configure environments, optimize performance and manage systems once they are operational.
Lenovo AI Express therefore extends beyond hardware with a portfolio of services designed to support the AI factory lifecycle.
These services can help organizations identify AI use cases, evaluate potential ROI and validate applications through proofs of concept. Once workloads are ready for production, Lenovo services can help optimize GPU environments for performance, utilization and cost efficiency.
The offering also introduces Premier Support Plus for Servers, which adds proactive and predictive support capabilities designed to identify potential issues earlier and help maintain operational continuity in mission-critical AI environments.
Together, these capabilities are intended to help organizations move from AI experimentation to production while reducing some of the operational complexity associated with building and managing AI infrastructure.
Built with NVIDIA
The collaboration with NVIDIA brings together Lenovo’s validated infrastructure configurations with NVIDIA accelerated computing, networking and AI software.
“As AI agents reshape every industry, enterprises need purpose-built infrastructure that can efficiently turn their data into intelligence,” said Chris Marriott, Vice President of Enterprise Platforms at NVIDIA. “Lenovo AI Express combines Lenovo’s validated systems with NVIDIA accelerated computing, networking and AI software into ready-to-ship solutions, giving organizations a faster path to deploy AI factories and scale as their workloads and demand for intelligence grow.”
The approach reflects a broader shift in enterprise AI. As organizations move from experimenting with generative AI toward deploying agents and other intelligent applications, infrastructure needs to support increasingly diverse workloads.
A standardized starting point can help organizations establish production capacity while retaining the flexibility to scale as adoption grows.
Expanding access through partners
Lenovo is also making AI Express available through its global partner ecosystem.
Through the Lenovo 360 framework, channel partners can access validated Hybrid AI Factory configurations and support customers throughout the sales and deployment process. This is designed to give partners a more straightforward way to identify AI opportunities and develop infrastructure solutions around specific customer requirements.
Availability, eligibility and ordering processes vary by region, with local guidance provided for participating markets.
Building a scalable foundation for enterprise AI
For organizations, the challenge is no longer simply deciding whether to invest in AI. Increasingly, the focus is on how to move successful AI experiments into production and scale them responsibly.
Lenovo AI Express addresses that transition by combining pre-validated infrastructure, NVIDIA technologies, enterprise software and lifecycle services into a more streamlined deployment path.
Customers can begin with a configuration aligned with their immediate requirements rather than investing in infrastructure far beyond their current needs. As models become more sophisticated, more employees use AI applications and inference workloads increase, the infrastructure can scale accordingly.
With Lenovo AI Express, the company is positioning its Hybrid AI Factory approach as a practical foundation for organizations looking to turn AI investments into production capabilities — while giving them the flexibility to adapt as their AI strategies evolve.
Source Link: https://news.lenovo.com/