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Case study / Healthcare

A global life sciences 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.

3,000

Servers monitored and managed under a single 24x7 operations model

3,900

Network devices covered across campus, data center, WAN, SD-WAN and wireless

35+

Countries supported from one global remote operations center

5 towers

Network, compute, cloud, backup and application infrastructure moved into one accountable managed services model

The complexity was structural, not technical

The challenge

The complexity was structural, not technical

More than 35 countries of manufacturing, research, enterprise applications and customer-facing services ran on an estate of 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.

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 procedures, limited automation, growing alert volume and lengthening resolution times, while operating costs climbed. The fragmented operating model also made it harder to hold service levels consistently, contributing to poor SLAs and customer satisfaction. Behind all of it sat unfinished strategic work: standardization, cloud governance, operational scalability, security posture and service-level compliance.

Why Gruve

Every tower, one accountable team

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

Assess the whole estate before touching any of it

Step 1

Structured assessment across people, process and technology

Discovery workshops, stakeholder interviews, infrastructure inventory, architecture review and tool evaluation across network, compute, backup, cloud and monitoring, producing a gap analysis, future-state architecture, transformation roadmap and formal knowledge transfer.

Step 2

Multi-tower operations transition

24x7 monitoring and management across enterprise network, server and compute, backup and disaster recovery, application infrastructure, and Azure and AWS cloud operations including cost optimization and security compliance monitoring.

Step 3

ITIL-aligned service management

Incident and major incident management, problem management, change support, capacity and availability management, root cause analysis, service reporting and continuous service improvement, under an executive governance framework.

Step 4

AI adoption and integration across routine operations

AI-enabled automation supported alert correlation, ticket creation, health checks, scheduled reporting, patch orchestration, backup validation and operational dashboards, helping teams reduce manual effort and adopt a more integrated operations model.

The outcomes

One operating model, one view of the estate

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

Stay split, or build a global 24x7 capability in house

Without this move, the estate would have carried on as it was: multiple infrastructure technologies run by separate internal 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.

What's next

Operations off the internal team, innovation back on it

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 delivery, a scalable support model, and more internal focus on strategic initiatives.

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.

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