Case study / Healthcare
A global life sciences and diagnostics leader modernizes IT operations across 3,000 servers and 3,900 network devices with one AI-enabled 24x7 managed services model.
Gruve unified fragmented infrastructure operations across network, compute, cloud, backup and applications, with ITIL-aligned governance, automation and continuous service improvement.
The Problem
Stakes and constraint
The customer is a global leader in life science research and clinical diagnostics, supporting hospitals, laboratories, pharmaceutical organizations and research institutions worldwide. Roughly 7,500 to 8,000 employees across more than 35 countries in the Americas, EMEA and APAC depend on infrastructure that runs manufacturing, research, enterprise applications and customer-facing services. As the global footprint expanded, that estate reached 3,000 servers and 3,900 network devices spanning on-premises data centers, Azure and AWS. The old state was multi-vendor and multi-tool, with limited visibility across the estate and no single-pane view of operations.
What made this hard for this organization specifically is that the complexity was structural, not technical. Multiple infrastructure technologies sat with separate teams and vendors, monitoring was split across several platforms, reporting was manual and visibility existed only in fragments. There was still no reliable correlation between infrastructure events and the business services they carried. The assessment found reactive incident management, manual health checks, inconsistent operational procedures, limited automation, growing alert volume and lengthening incident resolution times, while infrastructure operating costs continued to climb. The fragmented operating model also made it harder to hold service levels consistently, contributing to poor SLAs and customer satisfaction. On top of that sat unfinished strategic work: infrastructure standardization, cloud governance, operational scalability, security posture and service-level compliance. The requirement was standardized, ITIL-based operations delivered at global scale, so internal IT could move off day-to-day operations and onto innovation and business transformation.
Why Gruve
Rather than adding another tower-specific vendor to an estate already divided across teams and tools, the customer moved network, compute, cloud, backup and application infrastructure to a single partner running one ITIL-aligned model 24×7 from a global remote operations center. Gruve’s differentiation was the combination of multi-tower managed services, automation, governance and continuous service improvement in one model, tied to expected business outcomes: faster response, less manual effort, improved reporting and reduced operational risk. Executive governance and continuous service improvement were built into the operating model from the start rather than added later.
The Approach
The work, in four named steps
Step 1
Structured assessment across people, process and technology
Discovery workshops, stakeholder interviews, infrastructure inventory, architecture review, existing process assessment and tool evaluation covered the enterprise network, server and virtualization, backup and recovery, cloud and monitoring, producing a gap analysis, a future-state architecture, a transformation roadmap and formal knowledge transfer.
Step 2
Multi-tower operations transition
Gruve assumed 24x7 monitoring and management across the enterprise network (campus, data center, WAN, SD-WAN, wireless, VPN, network security, unified communications and contact center), server and compute (Windows, Linux, VMware, virtual machine lifecycle, Active Directory, DNS and DHCP, patching, OS hardening), backup and disaster recovery, application infrastructure (web, application, database and middleware), and Azure and AWS cloud operations including cost optimization, identity and access support and security compliance monitoring.
Step 3
ITIL-aligned service management
A standardized framework covering incident and major incident management, problem management, change support, capacity and availability management, root cause analysis, service reporting and continuous service improvement, delivered from a global remote operations center under an executive governance framework.
Step 4
AI adoption and integration across routine operations
AI-enabled automation supported alert correlation, incident ticket creation, health checks, scheduled reporting, patch orchestration, backup validation and operational dashboards, removing manual effort across the estate and helping teams adopt a more integrated operations model.
Environment supported
Cisco Catalyst, Nexus, ACI and SD-WAN, Versa SD-WAN, Palo Alto firewalls, F5 load balancers, Juniper routing, switching, firewalls and access points, AudioCodes SBC, Microsoft Teams, Dynamics 365 and Anywhere 365; VMware vSphere, Windows Server, Red Hat Enterprise Linux and SUSE Linux; Microsoft Azure and AWS; Veeam, Commvault and Veritas NetBackup; Nagios and SolarWinds; ServiceNow, Jira Service Management and Salesforce.
The outcomes
Value callout
Operational responsiveness
Faster detection of infrastructure events and faster incident response, with 24x7 monitoring, automated alert correlation and automated ticket creation
Reactive incident management, manual health checks, growing alert volume and lengthening incident resolution times
Cost per outcome
Centralized service management, standardized processes and automation across health checks, patch orchestration, backup validation and reporting.
Manual operational activity, manual reporting and rising infrastructure operating costs.
Control and sovereignty
One ITIL-aligned operating model with single-pane visibility across on-premises, Azure and AWS, plus cloud security compliance monitoring, identity and access support and executive KPI dashboards.
Multiple technologies run by separate teams, siloed management, several monitoring platforms and no correlation between infrastructure events and business services.
Risk reduced
Proactive backup operations with restore validation and disaster recovery support, automated incident workflows, improved application availability and fewer service disruptions.
Limited end-to-end visibility, increasing incident volumes and backup governance gaps.
The path not taken
Without this move, the estate would have carried on as it was:
multiple infrastructure technologies run by separate internal teams and external teams under a reactive model, monitoring split across several platforms, and reporting assembled by hand every cycle. The other option was to build an equivalent 24×7 global operations capability in house, across every tower and every region, while the same teams continued to absorb day-to-day operations.
Ongoing
Forward close
The engagement lifecycle runs from assessment and knowledge transfer through managed services transition into continuous optimization, with continuous service improvement built into the service management framework. The result is predictable managed services delivery, a scalable operational support model, more internal focus on strategic IT initiatives, and a foundation for future infrastructure transformation.
Who else this applies to: global life sciences and diagnostics organizations running hybrid estates across many countries, where internal teams are absorbed by day-to-day operations spread across too many separate technologies and tools.
