Rackspace Technology
rolled out AI Launchpad, a managed service built to help organizations move from early AI experimentation to something stable and production-ready. A lot of teams want to move faster with AI but get bogged down by infrastructure decisions, pilot creep, and the worry that whatever they build today won’t hold up later. Launchpad cuts through that noise by giving them a clear, secure path they can actually follow.
A Guided Path From Idea to Production
AI Launchpad breaks the journey into three steps: proof of concept, pilot, and production. Each phase sits on fully managed GPU infrastructure, Kubernetes clusters, and pre-installed AI/ML frameworks. This lets teams validate use cases, test workloads at scale, and deploy them in a controlled private cloud environment.
Bryan Litchford, VP of Private Cloud Solutions at Rackspace, told ChannelE2E that the platform is designed to reduce the friction enterprises typically face in early AI cycles.
“Running Proof of Concepts (POCs) and Pilots can be challenging, scopes can shift, and adapting to new tools can take time. The AI Launchpad simplifies this process with pre-installed, production-ready capabilities, enabling a seamless transition from POC to production. It also leverages the same architecture designs used in our large-scale AI Anywhere and AI Business platforms.”
Private Cloud Foundations for Security and Control
AI Launchpad builds on Rackspace’s AI Anywhere platform, which focuses on keeping data protected while maintaining performance across hybrid environments. It supports industries with strict compliance needs, giving them a private, isolated setup for training and running models.
Litchford emphasized that security is built in from the start. “AI Launchpad is a fully private solution, providing isolation at both physical and network layers. Rackspace also offers several connectivity options, such as RackConnect Global, that enable secure, high-performance links between private clouds and hyperscalers.”
A U.S.-based healthcare provider, Compass, followed this path as it moved from initial experiments into production. After hosting its core systems in Rackspace’s private cloud, Compass adopted AI workloads for natural language querying, automated documentation checks, and real-time reporting. The result was faster review cycles, improved documentation quality, and lower administrative overhead. It’s a clear example of how a structured approach can turn early interest into operational gains.
A New Opportunity for Channel Partners and MSPs
AI Launchpad isn’t just for enterprise IT teams. It also opens revenue paths for channel partners and MSPs that want to offer managed AI services without building the underlying infrastructure themselves.
“Our channel and alliance MSP partners can run services directly on top of the AI Launchpad or leverage it as a joint offering to end customers. To explore new opportunities, contact your partner account representative,” Litchford said.
Most organizations know they need AI but face delays tied to tooling, risk, and deployment readiness. AI Launchpad gives them a controlled environment, baked-in expertise, and a predictable path to real outcomes. For enterprises and partners alike, it shortens the distance between AI ambition and practical results.
