Accelerate AI adoption with Rackspace AI launchpad

Establish fully provisioned, managed and supported GPU compute, storage and networking resources. Each environment includes secure VPN access for remote teams and data scientists who need consistent performance and protection.

Configure Kubernetes clusters optimized for AI workloads and ready for scalable orchestration. Access a curated ecosystem of frameworks, libraries and development tools that support model development, testing and deployment across environments.

Start strong with clear documentation and best practices. Get direct guidance for cluster access, job submission and workflow setup. Our team assists with initial data uploads (storage only) and provides continuous environment monitoring, management and infrastructure-level troubleshooting. Each engagement includes up to 16 hours per month of Rackspace expert support during business hours.

Rackspace AI launchpad follows a structured three-phase model that helps you move from experimentation to production quickly and confidently. Each phase builds on the last, aligning infrastructure, performance and support to your stage of AI adoption.

Phase 1: Proof of concept
Validate your AI use cases in a secure, flexible environment before making long-term infrastructure commitments. The proof of concept (PoC) phase of Rackspace AI launchpad provides a lightweight, virtualized setup optimized for rapid experimentation and early insights.

Phase 2: Pilot
Move from experimentation to production readiness with access to high-performance, GPU-powered servers. The pilot phase helps teams fine-tune performance and reliability for real-world AI deployment, bridging the gap between testing and operational scale.

Phase 3: Production
Scale confidently with a fully operational, enterprise-grade environment built for consistent performance, security and throughput. The production phase integrates with solutions such as Rackspace AI Anywhere and Rackspace AI Business to support continued optimization and growth.