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Advisory services
Strategy from the people who will build it and run it.
Cloud and AI strategy for regulated and mission-critical enterprises. Determine where workloads belong, which AI use cases will pay back, how to govern them and what it takes to move from pilot to production. Our recommendations come from the engineers who will be accountable for operating the result.
from silicon to outcomes
Where Enterpise AI goes to production.
Rackspace is the operator of the full enterprise AI stack. We build, operate and continuously innovate AI environments that move AI into production while keeping you in control of your data, your technology choices and where your AI runs.
Enterprise AI Cloud
One stack. One operator. Full accountability.
Rackspace is the operator of the full enterprise AI stack. We build, operate and continuously innovate AI environments that move AI into production. We manage everything it takes to run there, from governance and security to performance and cost. And as enterprise AI evolves, we help you evolve with it.
Customer name achives measurable significant outcome with Rackspace's solutions and expertise
Advisory services
Strategy from the people who will build it and run it.
Cloud and AI strategy for regulated and mission-critical enterprises. Determine where workloads belong, which AI use cases will pay back, how to govern them and what it takes to move from pilot to production. Our recommendations come from the engineers who will be accountable for operating the result.
Healthcare
Modernize healthcare technology without disrupting care.
Text & Images
Everyone is selling AI. Few are accountable for what happens next.
Why Rackspace
The environment is governed. You stay in control. Rackspace stays accountable.
How we think about AI
Three levels of AI impact, and what each one needs underneath it
Most organizations are somewhere on this path. Advisory starts by deciding which level each initiative belongs at, what it will return and what it requires in data, infrastructure and governance.
AI advisory
From use case identification to governed AI solutions in production
Expert guidance to help you decide where AI will pay back, how it will be governed and what it needs underneath it.
Cloud strategy and operating model planning
We understand the foundations that AI strategy depends on.
Cloud and infrastructure strategy
Workload-by-workload placement across private, public and sovereign environments, assessed on cost, performance, data residency and operational fit.
Application modernization
Process First. Technology Second. A prioritized path through your application estate, led by the business processes that matter most.
Operating model, cost and risk
Governance structures, FinOps, security and risk assessment, and integration planning for mergers and acquisitions.
Control
Governance that never leaves the building.
Workloads
GPU-powered compute for your most demanding AI workloads.
Inference at scale
Language, vision and multimodal models serving applications and agents.
Fine-tuning
Smaller domain models trained on your data for better accuracy and fewer tokens.
Search and retrieval
Embedding and retrieval pipelines grounded in enterprise content.
Agents
Agentic workloads that call models repeatedly and need capacity that keeps pace.
Clinical and regulated AI
Imaging, summarization and document workloads on data that stays governed.
AI at the edge
Inference close to where data is created, in hospitals, branches and plants.
Situation
As the customer expanded, it needed its infrastructure to keep pace. The company ran databases on dedicated hardware and application workloads in virtualized environments. This hybrid environment delivered strong performance but introduced additional operational complexity.
Updating infrastructure, managing hardware lifecycle changes, and applying software upgrades required planned downtime, disrupting customer operations. These maintenance windows occurred multiple times per year, creating challenges for customers running 24x7x365 environments.
Updating infrastructure, managing hardware lifecycle changes, and applying software upgrades required planned downtime, disrupting customer operations. These maintenance windows occurred multiple times per year, creating challenges for customers running 24x7x365 environments.
To support continued growth, the customer needed to modernize its infrastructure, reduce downtime and maintenance complexity, and preserve performance, control and cost efficiency.
Solution
Rackspace Technology designed and delivered a modern software-defined data center (SDDC) environment that provided the customer with the benefits of cloud — automation, self-service and scalability — within a controlled private cloud model.
The engagement combined Rackspace Private Cloud Solution powered by Broadcom’s VMware Cloud Foundation with Professional Services and Managed Services, delivered as an outcomes-based project within a broader multiyear agreement. This simplified commercial complexity while aligning delivery with clear business objectives.
To meet an aggressive timeline, Rackspace procured and prepared the new infrastructure ahead of contract finalization. This proactive approach enabled an immediate project kickoff and eliminated delays associated with hardware readiness.
Rackspace migrated more than 1,200 virtual machines across approximately 90 structured migration events. The phased approach minimized risk, maintained service continuity and kept mission-critical systems operational throughout the transition. Rackspace worked closely with the customer’s teams at every stage, combining technical expertise with disciplined governance and coordination.
Customer is a [industry]-based organization focused on delivering [core products or services] to [target customers or markets]. With a growing presence across [locations, channels, or markets], Customer supports a broad range of business operations and customer needs.
As a Rackspace Technology customer, Customer continues to evolve its technology infrastructure to meet increasing performance expectations, industry requirements, and business demands. Its environment supports critical operations, including [key applications, workloads, or business processes].
Customer
Challenge
Industry
Outcome
Cards
Level 1
Efficiency
AI assists what people already do in HR, finance, legal, support and IT. Real value, quickly, on systems still designed for a person with a login.
Level 2
Workflow automation
Processes redesigned so systems talk to systems and agents make decisions inside defined limits. Where the operating model and governance questions get serious.
Level 3
Core business reimagination
Supply chain, clinical operations, lending and manufacturing rebuilt around what machines can do. The highest return, and the level that depends most on getting the foundation right.
AI strategy and use case prioritization
Readiness assessments and working sessions that surface use cases with defined business impact, then rank them by return, feasibility and risk.
AI governance and
responsible AI
Policy, controls, model and data governance, and audit evidence designed for regulated environments, so AI clears compliance review rather than stalling in it.
Data and infrastructure
readiness for AI
Gap analysis and roadmap for the data foundation and the governed infrastructure AI depends on: quality, lineage, access, placement and the platforms that make it run at scale.
Operating model
Build. Operate. Innovate.
GPU capacity only pays off when it is sized to the work, run every day by people who own the outcome, and refreshed as the hardware and software move. One team does all three.
Build
Sized and deployed
Capacity planned around your workloads, then provisioned and tested by the team that will run it.
Operate
Run like it's our own
GPU health, scheduling, security and lifecycle handled every day, with one team to call.
Innovate
Built to evolve
New accelerators and software brought in as they prove out, so capacity keeps pace with your models.
Control and authority
Choice
Economics
Speed to value
Outcomes
Right-sized
Options from edge and small-model inference to large-model inference and fine-tuning, so capacity matches the use case.
Governed by default
GPUs run in-region, in sovereign configurations or in your own facility, and your data never trains external models.
Open software
An open AI software ecosystem, so teams keep their choice of frameworks and models.
Operated end to end
Monitoring, drivers, firmware, lifecycle and capacity planning handled by Rackspace.
Kept productive
Workloads scheduled and shared across capacity to hold utilization high and cost per result low.
Connected to the stack
A direct path into managed inference, fine-tuning and data engineering, with the same team.
Operating model
Build. Operate. Innovate.
GPU capacity only pays off when it is sized to the work, run every day by people who own the outcome, and refreshed as the hardware and software move. One team does all three.
Rackspace plans, provisions and tests the environment, operates it as a managed service with one team to call, and brings in new accelerators and software as they prove out, so capacity keeps pace with your models.
Talk to a GPU specialistBuild
Sized and deployed
Capacity planned around your workloads, then provisioned and tested by the team that will run it.
Operate
Run like it's our own
GPU health, scheduling, security and lifecycle handled every day, with one team to call.
Innovate
Next generation, in place
New accelerators and software brought in as they prove out, so capacity keeps pace with your models.
01 · Assess
Diagnose and prioritize
Readiness assessments, working sessions and strategy reviews that produce a ranked plan with business cases attached.
02 · Prove
Pilot and Test
Co-create the first solution with your team, establish the technology stack and validate the business case against real data.
03 · Deploy
Put into production
Rackspace Forward Deployed Engineers embed in your environment to build, govern and deploy on infrastructure designed for regulated workloads.
04 · Operate
Run and improve
Day-to-day operations, cost and reliability owned by Rackspace, with learning fed back into the next use case.
Quotes & Testimonials
The Rackspace Technology team’s approach was fantastic. They have people who deeply know what they're talking about when it comes to AI and generative AI.
Alistair Gilbert
VP, Platform Engineering
The excellent collaboration throughout the project and our ongoing partnership with Rackspace have reinforced our confidence in selecting the right technology provider.
- Customer Name
Position, Company
Outcome
Today, the customer operates a highly available, secure server and SAP ECC environment on Google Cloud, supported by an ongoing managed services partnership with Rackspace Technology.
The customer’s transition to Google Cloud — spanning development, QA, production and reporting environments — was completed within an accelerated timeframe. The migration’s success was driven by cross-functional collaboration, technical expertise and disciplined project management.
The SAP platform, which supports critical business operations including logistics, warehouse management and labeling, experienced zero business interruptions throughout the transition. Technical challenges encountered during the migration were addressed quickly and efficiently, avoiding delays and minimizing operational risk.
Rackspace and Seattle Children's worked together closely to ensure that an appropriate configuration was built that factored in elements such as cost, the actual design performance of the environment, as well as ensuring that the redundancy really met our needs
- Nigel Hartell
Chief Architect, Seattle Children's
customer success
99.999% uptime for Epic on Rackspace private cloud
Featured Links to Pages
Enterprise AI Cloud
The governed infrastructure, platforms and engineers that take AI from pilot to production.
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Migration and Modernization
Workload placement decisions carried through to migration and ongoing operations.
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Managed Operations
Infrastructure and applications run 24x7x365, with one team accountable for the result.
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GPU-as-a-Service
Contracted AMD Instinct GPU capacity as bare metal, managed Kubernetes or on demand, built and run by Rackspace.
Forward Deployed Engineering
Engineers who work beside your teams to build, operationalize and continuously improve AI in production.
Private Cloud
Mission-critical private cloud on VMware Cloud Foundation, engineered around your requirements for control, security and performance.
Private cloud models
We helped pioneer managed private cloud, and we’ve run it every day for 25 years
Multi-Tenant
Shared VMware Cloud Foundation with isolated environments and capacity on demand.
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Bare Metal
Dedicated physical servers without a virtualization layer for performance-intensive workloads.
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Sovereign
Private cloud designed for strict data residency, control and sovereignty requirements.
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Hybrid Cloud
Private and public cloud connected under one consistent operating model.
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On-Premises
Private cloud operated by Rackspace in your data center or at the edge.
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Enterprise AI Cloud
Full-stack enterprise AI infrastructure and operations, from applications and agents to infrastructure.
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Industries
Trusted expertise for industries where the stakes are the highest
Healthcare
Epic and clinical platforms kept available, patient data protected, and a governed foundation ready to move AI from pilot to the point of care.
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Financial services
Core banking and payments modernized with proven recovery, data control and the audit evidence regulators expect, so AI can follow safely.
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Public sector
Sovereign, accredited cloud for citizen services, run by cleared teams, with the control to modernize today and adopt AI when you’re ready.
Learn More
Proof Strips / Stats
Years
Customers
Certifications
Megawatts
Years
Customers
Certifications
Megawatts
Years
Customers
Certifications
Megawatts
Years
Customers
Years
Certifications
Megawatts
VMware Cloud Foundation, run by one of its most experienced operators
Rackspace has run VMware for enterprises for more than 17 years and is among a limited set of Broadcom Advantage Partners delivering managed services on VMware Cloud Foundation. Licensing is included, the platform stays current and 400+ VMware certifications support the team operating it. For organizations rethinking their VMware strategy, Rackspace provides continuity on a platform their teams already know.
Years
Customers
Global
VMware Cloud Foundation, run by one of its most experienced operators
Rackspace has run VMware for enterprises for more than 17 years and is among a limited set of Broadcom Advantage Partners delivering managed services on VMware Cloud Foundation. Licensing is included, the platform stays current and 400+ VMware certifications support the team operating it. For organizations rethinking their VMware strategy, Rackspace provides continuity on a platform their teams already know.
Years
Customers
Global
Video
FAQ
FAQ
Common questions about AI and cloud advisory
What are Rackspace's Advisory Services?
Rackspace Advisory Services cover cloud and AI strategy for enterprises: AI use case prioritization and governance, cloud and infrastructure strategy across private, public and sovereign environments, data readiness, application modernization, operating model design, cost optimization, security and risk assessment, and integration planning for mergers and acquisitions.
Does Rackspace offer AI advisory services?
Yes. Rackspace AI advisory covers readiness assessment, use case identification and prioritization, AI governance for regulated environments, and the path from a first proven solution to production. It is delivered by Rackspace, the operator of the full enterprise AI stack from governed private cloud to AI inference and agents in production, with Forward Deployed Engineers carrying approved use cases into live operation.
How is Rackspace advisory different from a consulting firm or systems integrator?
Rackspace advisers are operators. The same company that recommends an architecture, a use case or a governance model builds it, runs it in production and stays accountable for cost, reliability and compliance. Recommendations are written to be operated, not handed off.
Does Rackspace recommend private cloud or public cloud?
Whichever fits the workload. Rackspace operates Amazon Web Services (AWS), Microsoft Azure, Google Cloud and Rackspace Private Cloud, and assesses each workload on data sensitivity, compliance, performance and cost. Most enterprises end up with a mix.
Which industries does Rackspace advise?
Rackspace advises organizations across all industries, especially on workload strategy, modernization and AI. Its deepest experience is in regulated and mission-critical sectors, including healthcare, financial services and public sector, alongside energy, manufacturing, retail and technology.
How does an advisory engagement start?
Typically with an AI readiness assessment or a cloud strategy assessment, followed by a working session that produces a prioritized plan with business cases. From there, Rackspace can prove a first solution, take it to production and operate it.
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Start with the decision in front of you.
Talk to a Rackspace advisor about where AI and cloud should take your business next, and what it will take to get there.
CONTACT US
Tell us the outcome you want to achieve. We’ll help you build the path to production.
Let’s talk about what’s next for you.
Share what success looks like for your business, and we’ll show you the path to get there.
Contact us and a Rackspace expert will follow up to help you get started.
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Partner ecosystem
Opinionated partnerships. Open by design.