An exclusive interview with Visionary Leader Kumar Gaurav Gupta, CEO of Verdantis, a software company building Agentic AI solutions for MRO Lifecycle Management

Traditional Computerized Maintenance Management Software (CMMS) has been a crucial part of industrial operations, and it has been around longer than one would believe. 

The roots of the very first CMMS system can be traced back all the way to the 1960s when work orders, maintenance schedules and spare part inventories were tracked through punch cards. 

Shortly after which, Punch Cards were replaced by computer terminals which were adopted by large companies but were still not widely available for organizations with large-scale and complex maintenance requirements.

The widespread adoption of Computerized Maintenance systems, that closely resemble what we use today, can be traced back to the 1970s, when the personal computer was introduced.

Coincidentally, or perhaps not, this is also the time when global manufacturing, particularly in the United States, witnessed its largest ever growth phase, creating immense wealth and solidifying the United States’ position as a powerhouse in global manufacturing.

The extent of impact that CMMS software played in this boom is debatable but there is no doubt that these software systems are a boon to companies in manufacturing, Energy, Minerals & Mining, Utilities and other asset-intensive operations with complex maintenance management requirements. 

However, as we progress further into the 21st century, experts and industry leaders have observed the limited pace of innovations in this space.

Today, we’re joined by Mr Kumar Gaurav Gupta, CEO of Verdantis, a known leader in data management software for MRO, that is evolving into a full-service MRO inventory software & CMMS, recently shared his insights on why the industry must rethink its approach to maintenance management.

While traditional CMMS software continues to hold a significant market share, adoption rates are slowing, and its efficacy is being questioned, particularly in industries that require real-time, accurate decision-making. 

It’s not enough to simply implement technology - it needs to be future-proof.

“The issue is that CMMS & EAM systems have become too compartmentalized. They’re isolated in silos, managing only maintenance data without integrating into broader business systems,” explains Kumar.

“This means it can't respond to changes in production schedules, demand fluctuations, or global supply chain disruptions, which are becoming more frequent.\

This signals a critical turning point in how maintenance software is approached. Industries need systems that can manage maintenance as part of a broader ecosystem.

There’s an urgent need for unified platforms that connect asset management, procurement, supply chain, and even production systems into a seamless experience,\ he notes.

The Role of AI in the Future of CMMS and Enterprise Asset Management

As industries move towards automation and digital transformation, Kumar is an advocate for AI’s transformative potential in maintenance management. 

He asserts that traditional CMMS models are inherently limited in their capacity to process and analyse the huge volume of data generated by modern operations.

\AI can play a game-changing role by enabling predictive maintenance, reducing unplanned downtimes, and optimizing asset performance,\ says Kumar. 

“AI’s ability to learn from historical data, environmental conditions, and even real-time operational changes will allow systems to predict potential issues before they arise- leading to both cost savings and improved operational efficiency.\

AI-powered CMMS can also improve decision-making by offering deeper insights into asset health, resource allocation, and preventive maintenance, all of which help businesses make better, more informed decisions.

Of course, this requires changes to the current architecture, reliable data and perfect synchronization of that data across disparate systems, but these are challenges we have been able to overcome

“This shift isn’t just about incorporating AI; it’s about having an AI-driven maintenance model that evolves and adapts as it learns from the data it processes,” Kumar highlights.

The goal with these modern Maintenance Software is to have AI do the heavy-lifting, and reduce human-errors, relegating humans to the capacity of a “Reviewer”

The Impact of in Global Supply Chains and Manufacturing Numbers

“With AI-driven CMMS and EAM systems, manufacturers can make informed decisions that allow them to quickly adapt to disruptions and mitigate potential risks before they materialize.

Through a combination of Integrated Agentic AI models across Intelligent Document Processing, Spare Parts Inventory Management and Data Management, we’re seeing very promising results as far as accuracy and autonomy in MRO operations is concerned.

The statistics speak for themselves.

The team at Verdantis have crunched the numbers across their product portfolio (detailed below)

1. Auto Enrich AI & Spare Seek AI – Autonomous Enrichment and Obsolescence tracker for MRO spare parts, saving months of hours that would otherwise require a subject matter expert to manually correct
2. Auto Doc AI – A “context-aware” intelligent document processing solution that can summarize and structure technical documents with a far better accuracy
3. Inventory 360 – AI Powered inventory management solution for MRO Spare Parts that can assess criticality of spare parts, fixed assets and autonomously manage inventory levels
4. Harmonize & Integrity [MRO Data Management Suite]

Based on assessment reports that have been run on anonymized client data across manufacturing and production-intensive industries, we’re seeing a 20-25% decrease in maintenance costs, driven largely by automations in maintenance procurement and more than 30% decrease in instances of outages and downtime.

In many instances, this number can increase significantly even beyond these thresholds.

We can attribute almost all these cost optimization strategies to AI-centric data management and maintenance management solutions

The Path Forward

As businesses move towards a more integrated, data-driven future, the industry needs to embrace the evolution of maintenance management.

The question isn't whether we need a fresh approach, but how quickly we can shift to smarter, more agile systems that can drive value, reduce waste, and improve overall efficiency.

His message is clear: as the world continues to change, so must the tools we rely on. 

The age of traditional CMMS is fading, and industries must evolve to meet the demands of the future. AI, clean data, and integrated systems are no longer optional - they are essential for survival in a competitive global landscape.

In conclusion, \The future is about embracing AI, not just for predictive maintenance, but as a cornerstone of intelligent manufacturing operations. A fresh approach to maintenance management is the key to unlocking the full potential of modern businesses.

The Journey Into Industry

Kumar Gaurav Gupta is a seasoned professional in enterprise software and the current Chief Executive Officer at Verdantis, a company specializing in enterprise software for Maintenance Management.

Kumar holds a degree from the Indian Institute of Management, Indore, and has held leadership roles at SAP, as the Country Manager for SAP Concur and VP of Strategic Initiatives & Spend Management for the APJ region.

With over two decades of experience leading P&Ls and driving measurable outcomes across industries, he is paving the way for the future of MRO operations with software systems embedded with Agentic AI capabilities.