Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I bring 22 years of experience leading large-scale Application Maintenance & Support (AMS) and digital transformation programs across retail and pharmaceuticals. At Walmart Global Tech, I transitioned a $15M vendor-led AMS operation in-house, scaling a 200-member GCC while reducing costs by 30% and driving GenAI-powered automation that eliminated tickets and improved efficiency by 30%. My expertise spans vendor-to-GCC transitions, ERP transformations, and SRE-driven operations—with a focus on operational resilience, automation, and scaling global support models for Fortune 500 companies.

Q2. How do you see the market for application maintenance and production support evolving in large retail enterprises, and which sub-segments are experiencing the fastest growth?

If you look at where application maintenance is heading in retail, the big shift is from cost arbitrage to value-driven operations. Ten years ago, it was mostly about labor arbitrage— “how cheap can I get support done.” Today, it’s about resilience, uptime, and how quickly you can recover from an issue without compromising the customer experience.
The fastest-growing areas I’m seeing are:
•  SRE-driven support. Instead of waiting for incidents, teams are moving toward proactive, alert-driven operations where the system tells you something’s off before customers feel it.
•    GenAI and ML-powered ticket elimination. This is no longer a buzzword. I’ve seen organizations achieve 30–40% productivity gains by allowing AI to automatically close tickets or prevent them from being raised in the first place.
•    Cloud-native operations. As POS, pharmacy, and e-commerce platforms move into the cloud, support models need to be scalable and cloud-first. The old way of patching servers or relying on vendor SLAs won’t cut it anymore.
In short, maintenance is no longer about “keeping the lights on.” It’s about keeping systems invisible to the customer—always-on, resilient, and able to scale seamlessly when the business does.

Q3. How are digital transformation trends impacting POS, pharmacy, and other critical retail applications, and what opportunities exist for further innovation?

First and foremost, in the AI era, a unified customer journey across in-store, online, and mobile is no longer optional—it’s a mandate. Customers expect a seamless transition from one channel to another, and retailers who fail to deliver this experience will quickly lose relevance.
Here’s how I see digital transformation reshaping the core applications:
•    POS systems are evolving from heavy, hardware-bound terminals to cloud-native, mobile-first platforms. These are faster to scale, easier to update, and can do things like real-time inventory visibility or dynamic pricing at checkout.
•    Pharmacy platforms are being tightly integrated with EHRs, telehealth, and automated refills, which is making the experience both more customer-centric and more compliant with healthcare regulations.
•   Back-office retail applications are benefiting from AI-driven forecasting, fraud detection, and hyper-personalized engagement, giving businesses sharper insights and faster decisions.
And the real game-changer? Predictive and automation-first operations. Imagine zero-downtime retail, where AI predicts an outage before it happens or pharmacy workflows that are fully automated to ensure patient safety and regulatory compliance. That’s where the big opportunities lie—not just in digitizing existing processes, but in reimagining how retail operates end to end.

Q4. In what ways are initiatives like energy-efficient systems, server optimization, or green cloud adoption reducing operational carbon footprints?

Honestly, I see sustainability no longer as an option—it’s become a real buying decision factor. When I talk to peers in the industry, this comes up more and more.
Take energy-efficient infrastructure—it directly brings down cost of ownership while keeping you aligned with ESG mandates. Then you’ve got green cloud adoption. Many workloads today are transitioning to providers that run on renewable energy, making your operations greener by default. And with server optimization and workload consolidation, you’re simply cutting the fat—reducing idle capacity and in some cases dropping carbon footprints by 25–30%.
For me, the key point is this: it’s not just about compliance anymore. Green IT is a cost lever and a competitive differentiator. If you can show that you’re reducing spend and running sustainably, you’ll not only win on efficiency—you’ll also attract ESG-focused investors, customers, and even talent who want to work for a purpose-driven enterprise.
At the end of the day, going green isn’t just the right thing to do—it’s the smart business move.

Q5. How critical are factors like post-deployment support, response times, and customization flexibility in shaping purchasing decisions?

In my view, buying decisions today aren’t just about features or functionality anymore—they’re really about resilience and adaptability & maintainability.
Take post-deployment support. This is a huge differentiator. If the support isn’t substantial, it’s a deal-breaker. And honestly, the production support or operations team should be involved right from pilot deployments. That’s the only way you can guarantee smooth post-go-live support and resolve issues swiftly without impacting business.
Then there are response times. In retail, every minute of downtime translates to lost sales and frustrated customers. So fast recovery isn’t a nice-to-have; it’s survival.
And finally, customization flexibility. No retailer wants an out-of-the-box, one-size-fits-all solution. Whether it’s POS, pharmacy, or e-commerce, they need tailored workflows that match their business processes.
That’s why when I look at RFPs, I see things like uptime SLAs, MTTR (mean time to recover), and support responsiveness being given as much weight—sometimes even more—as the product’s core features. At the end of the day, it’s not just about what the product does; it’s about how well it runs once it’s in production.

Q6. Which companies or vendors are pushing the boundaries in automation, self-healing systems, or predictive analytics, and what makes their approach stand out?

From what I see, the leaders are the ones who are embedding autonomy straight into operations. A few examples come to mind:
•    ServiceNow, with its predictive intelligence and automated workflows.
•    Dynatrace and New Relic for AI-powered observability and self-healing alerts
Now, what actually makes them stand out? It’s the shift from reactive monitoring to predictive self-healing. If a service provider is still talking about ticket volumes and resolution times, that tells me they’re stuck in reactive mode. And reactive support always comes with escalations, customer frustration, and brand impact.
The real differentiator is when the customer never even feels an issue—because the system already detected it, contained it, or resolved it proactively. That’s where embedding GenAI agents into operations is game-changing: tickets get resolved without human intervention, sometimes before they’re even logged.
And another significant point—they’re not building point solutions. They’re building ecosystems that integrate observability, automation, and AI into one platform. That’s what allows true scalability and resilience.
In short, the vendors who are moving the needle are the ones who don’t just help you respond faster—they help you avoid the issue altogether.