By: Harsh K. Ved, Senior Specialist - Cloud & Infra Management

In today’s digital-first world, IT operations are all about keeping the lights on, since they are central to business continuity, agility, and innovation. As enterprises scale across hybrid and multi-cloud environments, the complexity of managing infrastructure, applications, and data has grown exponentially. Traditional monitoring and manual troubleshooting approaches are proving inadequate in the face of this complexity, leading to increased downtime, delayed decision-making, and rising operational costs.

This is where AIOps (Artificial Intelligence for IT Operations) steps in, not as a tool, but as a transformative strategy. AIOps combines machine learning, advanced analytics (real-time and historical), and automation to enable IT teams to move from reactive incident management toward proactive, predictive, and increasingly autonomous operations. It enables faster root cause analysis, predictive incident prevention, and intelligent automation of routine tasks, freeing teams to focus on strategic initiatives.

We believe AIOps is about operational efficiency and empowering IT to become a strategic enabler of business outcomes. In this blog, we showcase how AIOps principles were applied to solve three high-benefit challenges in Veeam operations for our clients. By Veeam operations, we refer to the critical activities involved in managing Veeam backup environments, such as monitoring backup jobs, ensuring license compliance, maintaining documentation, and troubleshooting issues. These tasks are essential for data protection and business continuity, and we applied AIOps principles to make them smarter and more automated. The solutions demonstrate how AI, automation, and data-driven insights can deliver measurable value, quickly and securely.

Challenge 1: Fragmented knowledge across Veeam documentation and SOPs

Figure 1: Veeam Knowledge Hub (Generated using text-to-image prompt via CoPilot)

In today’s hybrid IT environments, engineers are expected to troubleshoot, upgrade, and maintain systems with speed and precision. However, the reality is often far from ideal. Critical information is scattered across vendor portals, knowledge base (KB) articles, internal SOPs, and tribal knowledge. This fragmentation leads to inefficiencies, delays in resolution, and increased risk of non-compliance or data exposure.

The challenge is compounded when engineers navigate multiple systems for routine tasks, such as resolving Network File Copy (NFS) stream issues, accessing backend database configurations, or performing compliance checks. For our client, the absence of a unified knowledge framework slowed down operations and created dependencies on individual expertise, making scalability and governance difficult.

Solution: Veeam Knowledge Hub

To address this challenge, we introduced Veeam Knowledge Hub —a CoPilot-powered, AI-driven Q&A platform that centralizes and governs operational knowledge. This solution is designed to deliver instant, vendor-verified answers to engineers using a natural language interface, eliminating the need to search across disparate sources manually.

Key features

• Natural language Q&A interface
• Integration with Veeam official documents, KBs, and SharePoint SOPs
• Guardrails to ensure vendor content is authoritative
• Metadata strategy, naming standards, and audit logging

Benefits:

• Efficiency: ~15–20% time saved per activity
• Compliance: Zero risk of sensitive data exposure
• Scalability: Ready for multi-team and account-level rollout

Challenge 2: License visibility blocked by Splunk integration delays

In enterprise IT environments, license management is a critical yet often overlooked function. Accurate visibility into license utilization directly impacts forecasting, procurement decisions, and audit readiness. While automation for license data collection may exist, the real challenge lies in transforming that data into actionable insights, especially when dependent on external platforms. To this end, we introduced Splunk, a data analytics platform that aggregates and indexes data for near real-time visibility, as the designated tool to centralize Veeam data.

In the case of Veeam operations, although automation pipelines were in place, the insights remained locked for over six months due to Splunk deployment delays. This bottleneck forced LTIMindtree’s operation teams to rely on manual methods for forecasting and audit preparation, leading to inefficiencies, delayed decisions, and increased compliance risk. For our client, the inability to act on existing data in real-time created a gap between operational needs and infrastructure readiness.

Solution: Veeam License Analyzer

Figure 2: Veeam License Analyzer (Generated using text-to-image prompt via CoPilot)

To overcome this challenge, the Veeam License Analyzer was launched – an AI-powered solution that decouples license insights from infrastructure dependencies. This tool consolidates license data from existing automation pipelines and transforms it into a single source of truth for utilization tracking and forecasting.

Key features

• Reuses existing automation as a system of record
• Consolidates data in seconds
• Flags under/over-utilization
• Enables regression-based forecasting
• Fully decoupled from Splunk

Benefits

• Speed: Same-day insights replacing months-long delays
• Efficiency: 24+ man-hours saved annually (excluding automation gains)
• Decision support: Faster, data-driven decisions for ops and procurement
• Compliance readiness: Streamlined audit prep

Challenge 3: Streamlining inventory data access for operational efficiency

Inventory data is usually fragmented across Excel sheets and the ServiceNow CMDB (SNOW CMDB), making it difficult to retrieve specific server or business unit details quickly. This manual process becomes cumbersome, especially during urgent operations or compliance checks, leading to delays and inefficiencies.

Solution: Veeam Infra Inventory Management

To streamline access and improve responsiveness, an AI-powered chatbot – ‘Veeam Infra Inventory Management’ was proposed to our client. This chatbot can interpret natural language queries and fetch detailed inventory data by integrating with both Excel and SNOW CMDB. It provides instant access to critical infra information such as operating system, IP address, domain name system, subnet, license details, vendor info, and hardware warranty status.

Key features

• Natural language query support for intuitive interaction
• Integration with Excel and SNOW CMDB for comprehensive data access
• Real-time retrieval of server and business unit details
• Audit logging for compliance and traceability
• Scalable architecture to support future inventory modules

Benefits

• Reduces query time from ~5 minutes to under 1 minute
• Cuts manual lookup effort by 80%
• Enhances compliance visibility with 100% traceable audit logs
• Lowers operational overhead by an estimated 25%
• Improves decision-making speed during critical operations

Shared characteristics of all three solutions

• AI with strict content controls
• Measurable operational benefits
• Fast scale-up across teams and business units

Conclusion: Smarter operations, strategic benefits

The shift to AIOps is more than a technical upgrade; it marks a strategic transformation in how enterprises approach IT operations. In an era defined by complexity, scale, and speed, traditional reactive models are no longer sufficient. Organizations must evolve toward intelligent, proactive operations that resolve issues faster and anticipate and prevent them.

By embedding AI and automation into IT workflows, enterprises gain the ability to make real-time decisions, reduce manual effort, and ensure compliance across environments.

Veeam Knowledge Hub, Veeam License Analyzer, and Veeam Infra Inventory Management—demonstrated how targeted AIOps interventions can deliver tangible outcomes: faster insights, measurable efficiency gains, and audit-ready compliance.

As IT ecosystems grow more distributed and dynamic, the ability to scale intelligent operations securely and rapidly will define future-ready enterprises. AIOps is about solving today’s problems and building resilient systems that learn, adapt, and drive business outcomes. It empowers IT to shift from being a cost centre to a strategic enabler of innovation, agility, and growth.

Enterprises that embrace AIOps today will lead the future of intelligent operations, building resilient, adaptive systems that turn IT into a driver of innovation and growth.

References

Configr Technologies. AIOps, What Is It, and Why Does It Matter to IT Operations. Medium. https://configr.medium.com/aiops-what-is-it-and-why-does-it-matter-to-it-operations-d7c630233fce

Fenjiro, Youssef. Machine Learning and IT Infrastructure Management Automation (AIOps). Medium. https://medium.com/@fenjiro/machine-learning-and-it-infrastructure-management-automation-4c4c06e213b9