We deliver continuous operations and ongoing improvement of your business-critical IT services – reliable, measurable and audit-ready. Our managed services follow ITIL 4 and modern SRE principles, safeguarding realistic SLAs, clear responsibilities and a transparent KPI system. Agile methods, clean service governance and disciplined automation with Power Automate and RPA reduce manual effort and accelerate service delivery. In addition, we deploy AI assistants for requirements analysis, log-data assessment and knowledge management – privacy-compliant and with human-in-the-loop review. Regulatory demands from MaRisk, DORA and ISO 27001 are baked into our steering logic, not bolted on later. In this way we combine stable run operations with measurable cost optimisation and a roadmap for scale and digital transformation.
Overview
Why managed services?
IT landscapes grow more complex, regulatory demands (DORA, MaRisk, ISO 27001) intensify, and skilled staff remain scarce. At the same time, costs must stay transparent and services available around the clock. Managed services provide a dependable framework: defined service levels, clear responsibilities, automated processes and a manageable KPI system.
Vetrexa combines structured IT operations with continuous improvement. We take over monitoring, incident resolution, patch and security management, and unlock efficiency through automation (Power Automate, RPA) and AI assistants. The outcome: stable services, lower run costs and a resilient foundation for growth and transformation.
Managed services can be distinguished by delivery model. In the managed-capacity model we provide agreed capacity, skills and resources for operations and evolution – flexibly scalable, with clear roles and backlog steering. In the managed-outcome model we own defined results and service qualities instead, measured against SLAs, KPIs and business outcomes such as availability, cycle times or case closures. The choice of model follows the maturity, compliance envelope and value contribution of the service. For time-critical environments we complement this with a follow-the-sun model: responsibility travels between European and international sites with defined hand-over points, so that incidents are worked without lost time. To improve service quality we lean firmly on shift-left support: knowledge, automation and self-service are pushed as far as possible towards the user or to level 1, relieving levels 2 and 3 and shortening cycle times. Concretely, that means well-maintained runbooks, ChatOps integration, a central knowledge-article estate and clearly defined escalation paths in an incident bridge for major incidents. The result is a service delivery model that is at once resilient, transparent and economical – and is anchored in your governance with unambiguous reporting rules.
Our scope
What we deliver
01
IT Operations, Monitoring & Incident Resolution
Stable run operations with clear processes, active monitoring and fast incident handling – aligned with ITIL 4 principles. We orchestrate incident bridges for major incidents, connect recurring disruptions through problem-ticket chaining and maintain runbooks and knowledge articles as a living knowledge base. Alerts flow into Ops teams via ChatOps so that response times stay short and hand-overs between shifts remain lossless.
Incident, problem and change management
Monitoring and alerting (Kibana, ServiceNow)
Runbooks and knowledge management
On-call and escalation models
Reporting on availability and performance
Problem-ticket chaining and root-cause analysis
ChatOps and incident-bridge management
02
Security Management & Patch Management
We keep your systems current and compliant – from automated patch cycles and SIEM integration through to resilient vulnerability management. Hardening baselines, configuration-drift control and documented exceptions safeguard auditability; reports for MaRisk, DORA and ISO 27001 emerge from a single source of truth. Vulnerabilities are prioritised by exposure, CVSS and business impact – not by the patch calendar alone.
Patch and vulnerability management (MECM)
SIEM integration and log analysis
Hardening of server and client environments
Security reporting for audit and supervisors
Contingency and recovery concepts
Vulnerability prioritisation by business impact
Compliance reporting for MaRisk, DORA and ISO 27001
03
Service Governance, SLAs & KPI Reporting
Transparent steering of your services with clear objectives, measurable KPIs and regular reviews at three levels: operational, tactical and strategic. We model SLAs, OLAs and UCs consistently and translate them into Power BI dashboards that put the business and IT view on the same data. Governance rituals, clear roles (service owner, process owner) and a documented escalation matrix make steering predictable and audit-ready.
SLA and OLA design
KPI and compliance dashboards (Power BI)
Service catalogues and charging models
Service reviews with business units
Continual service improvement (CSI)
SLA / OLA / UC modelling including escalation matrix
Governance rituals at three levels (ops, tactical, strategic)
04
Process Optimisation & Automation (Power Automate, RPA)
We identify repetitive tasks and replace them with robust, maintainable automations built on Power Automate, Power Automate Desktop and RPA. On the infrastructure side, we rely on Infrastructure as Code (IaC) with Terraform so that environments are versioned, reproducible and audit-safe. An Automation Centre of Excellence secures reuse, quality and maintainability – from discovery backlog through to bot lifecycle.
Process analysis and automation potentials
Delivery with Power Automate and Power Automate Desktop
RPA bots including operations and monitoring
Integration with ServiceNow and back-office systems
Automation governance and reuse
Infrastructure as Code (IaC) with Terraform
Automation CoE with bot-lifecycle management
05
Agile Transformation & Customer Collaboration
We bring agile methods into operations – from Kanban boards for Ops teams through Scrum-of-Scrums to SAFe programmes for ongoing evolution. WIP limits, flow metrics and regular retrospectives turn incident collection into a controlled flow. Close collaboration with business units through service reviews, PI planning and priority boards makes backlog steering transparent and outcomes dependable.
Kanban and Scrum setup for operations and maintenance
SAFe programmes for operations and change teams
DevOps practices and CI/CD in operations
Retrospectives and continuous improvement
Close collaboration with business units
Flow metrics and WIP limits in operations
PI planning and priority boards with business units
06
AI-Assisted Tools in Consulting
We use LLM-based copilots to make analysis, documentation and reporting more efficient and consistently high in quality. Prompt engineering, curated prompt templates and Retrieval-Augmented Generation (RAG) over client knowledge bases raise output quality substantially. Guardrails, content filters and human-in-the-loop review safeguard compliance with GDPR, MaRisk and internal policies.
Requirements and anomaly analysis with LLMs
Automated documentation and report generation
Test case design and code reviews
Privacy-compliant model operations (GDPR)
Guardrails, governance and human-in-the-loop
RAG over client knowledge bases and runbooks
Prompt templates and guardrails for compliance
Method
Our approach in 4 phases
01
Assess
We analyse operating processes, tool landscape, SLAs and regulatory demands – as the basis for a viable target picture.
02
Onboard
Structured take-over of services: runbooks, access, monitoring, ownership and governance are established.
03
Operate
Reliable run operations along ITIL: incident, problem and change management, security and patch management, KPI reporting.
04
Optimise
Continuous improvement through automation, AI tools and regular service reviews – measurable and steerable.
Metrics
SLAs & KPIs in detail
MTTA / MTTR / MTBF
Mean Time to Acknowledge, Mean Time to Restore and Mean Time Between Failures form the heart of any resilient SLA system. MTTA measures how quickly an alert is acknowledged; MTTR the restore time from incident start to service recovery; MTBF the average time between two failures as a stability indicator. We correlate these metrics with change and deployment data so root causes become visible and improvements steerable.
First-Call Resolution & Escalation Rate
First-Call Resolution (FCR) measures the share of tickets resolved on first contact – a direct indicator of knowledge quality and tool maturity. The escalation rate shows how often incidents leave the intended support level, exposing weaknesses in ownership and runbooks. We steer both KPIs together with knowledge management so self-service and level 1 are strengthened and higher levels relieved.
Automation Ratio & Deflection Rate
The automation ratio quantifies the share of tickets closed fully by automation; the deflection rate the share of requests resolved by users themselves through self-service portals, chatbots or knowledge portals. Both are core indicators for shift-left support and the effectiveness of RPA, Power Automate and AI assistants. We track them continuously in Power BI dashboards and tie them to concrete optimisation programmes.
References
Managed services project experience
Selected project references by industry – without naming clients.
Aerospace
IT & Compliance Taskforce – SAFe
Carve-out compliance with six squads in a SAFe setup, SIEM/SOC integration, AI-assisted monitoring and a Windows 10 client rollout – delivered audit-ready and at scale.
COBIT-based governance with audit-ready recertification processes and Power BI dashboards for ongoing KPI steering towards auditors and supervisors.
Toolset: ServiceNow, Jira/XRay, Confluence, Power BI
Method: COBIT, MaRisk, KPI reporting
Industry / IT Services
Process Automation & RPA
Analysis and delivery of automation potentials across recurring back-office and IT processes with Power Automate and RPA – including operations, monitoring and governance.
Toolset: Power Automate, RPA, ServiceNow, Power BI
Method: process analysis, automation governance, CSI
Automotive
24/7 SOC Operations
Design and operation of a 24/7 security operations centre for an international automotive supplier – follow-the-sun across European and international sites, SIEM/SOAR integration, AI-assisted alert triage and weekly threat reviews. Hand-overs, runbooks and incident-bridge concepts documented in an audit-ready fashion.
Toolset: SIEM/SOAR, Kibana, ServiceNow, Power BI
Method: ITIL 4, ISO 27001, SOC playbooks
Public Sector
Managed Service for Digital Citizen Services
Operations and evolution of a regional authority's digital citizen services – availability targets aligned with BSI baseline protection, accessibility reviews and change-freeze calendars around election periods. Automation of recurring ticket categories with Power Automate and deflection via a self-service portal.
Toolset: ServiceNow, Power Automate, Kibana, Power BI
Setup of a DORA level-2 compliant managed service for an insurer: continuous monitoring of critical ICT services, standardised ICT-incident classification, and ICT-incident reporting to the supervisor within 24 hours. Dashboards for resilience metrics and third-party risk views in Power BI, coupled with the ongoing KPI reporting.
Business and IT strategy, cloud target architecture and governance frameworks – the frame for efficiency and scale in operations.
AI in operations
AI in consulting — practical approaches
LLM-based assistants are not a gimmick in our consulting practice but an integral part of the delivery model. They support consultants and Ops teams with requirements analysis, test case design, log assessment, documentation and knowledge retrieval – from intake with the business through to operational day-to-day. In this way we accelerate analysis, reduce duplicated effort and materially raise the consistency of deliverables.
A central building block is Retrieval-Augmented Generation (RAG): instead of letting a model answer from generic world knowledge, we load it at runtime with the relevant excerpts from client-specific knowledge bases. Runbooks, process handbooks, MaRisk or DORA obligations and internal policies are ingested into a vector database and made available in the context of the question in a controlled way. The result: traceable, defensible answers with source citations – no hallucinating in a vacuum.
To keep quality reproducible we work with versioned prompt templates. They encapsulate role, task, format constraints, examples and fallback behaviour and are maintained like source code: reviewed, tested and released. For standard cases such as ticket classification, log triage or regulatory checks, reusable building blocks emerge that provide consultants and Ops teams with productive AI support immediately.
Guardrails secure responsible use. We deploy input and output filters for sensitive data, define permitted and prohibited topic areas and log usage for audit and compliance. Human approvals (human-in-the-loop) remain mandatory wherever decisions touch regulation, client communication or changes to production systems. In this way we combine efficiency gains with traceability and regulatory certainty.
FAQ
Frequently asked questions
How do you secure SLAs in operations?
We work with clearly defined service-level targets, KPI-based monitoring and regular service reviews. Response and resolution times are measured transparently via ServiceNow and SIEM systems (including Kibana), consolidated into Power BI dashboards and aligned with your business units through a structured governance process.
Which automation tools do you use?
We favour Microsoft Power Automate, Power Automate Desktop and selected RPA platforms for process automation. For IT automation and operations we use ServiceNow workflows, MECM as well as PowerShell and script-based automation – embedded in a robust automation governance.
How do you use AI assistants in consulting?
We use LLM-based assistants for requirements analysis, documentation, test case design, data analysis and code reviews. The models run in a privacy-compliant environment – client data is not shared with public models. This unlocks efficiency without compromising compliance obligations such as GDPR or MaRisk.
Do you offer 24/7 operations?
Yes. Together with our partner network we deliver flexible service windows – from classic 8/5 operations to 24/7 models with defined on-call rotations. Scope, response times and escalation paths are agreed individually in the service catalogue and SLA.
How do you measure managed service quality?
Resilient service quality is measured through a balanced set of metrics: MTTA, MTTR and MTBF for response and stability, First-Call Resolution and escalation rate for process maturity, automation ratio and deflection rate for efficiency, and CSAT/NPS for perceived service quality. These KPIs are consolidated in Power BI dashboards, discussed in operational, tactical and strategic service reviews and translated into concrete improvement actions.
What is RAG and how do you use it in support?
Retrieval-Augmented Generation (RAG) combines LLM answers with your own knowledge base: runbooks, knowledge articles, process handbooks and regulatory obligations are stored in a vector database and injected into the prompt at runtime with a tight fit. In support, RAG accelerates ticket classification, log triage and root-cause analysis and secures traceable answers with source citations – without client data flowing into external training data.
Can AI assistants replace level-1 support?
No, they complement it. AI assistants take over standard classifications, first responses and suggestions based on runbooks and knowledge articles, thereby lifting the deflection rate and first-call resolution. Human level-1 support remains indispensable for empathy, ambiguity, regulation and exceptional cases – we design the collaboration as a copilot model with human-in-the-loop, clear hand-over logic and continuous quality measurement.
Ready for stable services and more automation?
Let's discuss your operations and automation roadmap – informally and at eye level.