Skip to main content
  1. Contributor Content

Architecting the data backbone for AI-Powered quick service innovation

By , Content Contributor
headshot of Gowtham Kumar Reddy Mittoor
Gowthamkumar Reddy Mittoor / Gowthamkumar Reddy Mittoor

In today’s data-fueled business landscape, enterprises face the dual challenge of managing explosive data growth while extracting meaningful insights to drive innovation. Gowtham Kumar Reddy Mittoor, a Senior Data Engineering Leader, has played a key role in developing scalable data platforms that help organizations make better use of their data resources.

As the Senior Manager of Data Engineering and Visualization, Gowtham heads a dynamic team of accomplished data engineers and visualization experts that are delivering solutions for quick and smart decision making throughout the enterprise. His responsibilities include the design and deployment of a strong data infrastructure, democratization of analytics through self-service platforms, and advanced practices into core business processes.

Recommended Videos

Gowtham’s signature contribution is in his leadership role in developing Customer Data Platforms (CDPs), which are centralized systems for unifying customer data across digital, in-store, and third-party touchpoints. Such platforms give organizations a 360-degree view of the customer, allowing for hyper-personalized marketing and real-time engagement strategies, as well as significantly improved customer retention.

Related: 
Best new movies to stream on Netflix, Hulu, Prime Video, HBO Max, and more

“CDPs are not just a technical solution, they’re a strategic capability,” says Gowtham. “By centralizing and activating customer data, businesses can unlock new levels of personalization, loyalty, and revenue growth. It’s about making the customer the center of every decision.”

These platforms have built improvements in the management of data in retailing, quick-service restaurants, and financial services industries from evolving customer-profiles and from becoming an agile player in data. Gowtham’s contribution has supported enterprises in improving their targeting accuracy, journey optimization among customers, and realization of ROI from marketing spend.

However, one of Gowtham’s key projects involved designing a data ecosystem that supports AI-powered, automated drive-thru ordering for quick-service restaurants (QSRs). By leading the development of a resilient, real-time data architecture, Gowtham laid the foundation that allows voice AI systems to seamlessly integrate with point-of-sale platforms, customer profiles, and kitchen operations.

“This isn’t just about technology—it’s about reimagining the customer experience,” Gowtham explains. “With AI-powered ordering, we’re collapsing wait times, increasing order accuracy, and enabling truly touchless service. And none of that is possible without the right data engineering underneath.”

His solution integrated real-time streaming, robust identity resolution, low-latency decision engines, and predictive models—creating a production-grade architecture that supports AI-driven decision-making at the speed and scale required by high-volume restaurant environments. This accomplishment played a role in organizational progress and coincided with developments in the Quick Service Restaurant (QSR) industry, where automation and data intelligence work hand in hand to drive efficiency and elevate service.

Through his work, Gowtham has contributed to advancements toward more automated drive-thru operations in the industry. In this future, AI, data, and automation converge to deliver frictionless, personalized, and scalable guest experiences. His work illustrates possible strategies for digital adoption in the QSR industry and beyond.

Beyond customer analytics and AI enablement, Gowtham has delivered enterprise-wide impact by developing self-service analytics platforms for finance and operations. His solutions have enabled business users to access real-time insights through intuitive dashboards, reducing reliance on engineering teams and accelerating decision-making cycles.

His architectural approach emphasizes scalability, resilience, and performance—key pillars that allow organizations to grow without reengineering their data foundation. Gowtham has been instrumental in transitioning data ecosystems to cloud-native architectures, reducing infrastructure costs while improving speed and accessibility.

His frameworks have become models of data-driven modernization, helping businesses transition from legacy bottlenecks to agile, insight-driven operations. Gowtham is also a vocal champion for data governance and compliance, ensuring that organizations remain secure, ethical, and aligned with regulatory standards as data capabilities expand.

His embrace of emerging technologies complements his leadership in engineering. By embedding predictive analytics and machine learning into data workflows, he has helped enterprises anticipate trends, forecast demand, and proactively address operational bottlenecks.

Looking ahead, Gowtham is exploring real-time analytics, data fabric architecture, and AI-driven automation to build next-generation data systems. His future-forward mindset ensures that the platforms he builds are optimized for today’s challenges and resilient to tomorrow’s disruptions.

“The data landscape evolves fast, but with the right foundation, organizations can stay ahead of change instead of reacting to it,” he reflects. “My goal is to help businesses become not just data-driven, but data-confident.”

Gowtham Kumar Reddy Mittoor’s work exemplifies the strategic role of data engineering in modern enterprise transformation. By focusing on platform development, user-oriented design, and effective leadership, he has contributed to systems that meet business needs and respond to changes in AI and automation.

Digital Trends partners with external contributors. All contributor content is reviewed by the Digital Trends editorial staff.
Chris Gallagher
Chris Gallagher
Chris Gallagher is a New York native with a business degree from Sacred Heart University, now thriving as a professional…
Will the future of data entry be entirely controlled by AI? Long-time industry expert weighs in

There’s no doubt that artificial intelligence is changing the world. AI’s potential to automate many tasks that are being done by humans is unparalleled, and it is expected to contribute $15.7 trillion to the global economy by 2030. With such a wide-reaching impact, some roles will inevitably be made redundant by businesses adopting AI into their operations. Some experts believe that data entry is one of these jobs, due to being composed mostly of simple, repetitive tasks.

Many businesses are turning to AI because of increased speed and cost savings, and it allows the business to allocate its human resources to other tasks. However, AI is not a silver bullet that can perform all needed tasks without the need for human intervention. Alan Bandell, Founder and CEO of Axion Data Services, an industry leader in providing data entry outsourcing services to companies all over the US, believes that the future of data entry will be intertwined with and majorly transformed by AI, but it won’t make human expertise obsolete.

Read more
KonnektVPN: The VPN solution powered by blockchain and AI
konnekt vpn konnektvpn

As AI technology has become more rampant recently, innovation is certain, with many networks announcing updates and upgrades regularly. However, KonnektVPN, a VPN provider startup, has announced its AI virtual private network (VPN), aimed at enhancing online connectivity and security.

With an emphasis on user safety and privacy, KonnectVPN provides cutting-edge security measures and state-of-the-art features, creating a safe platform where users can comfortably use the internet for various purposes without fear of losing their data or assets. The network's security prevents DNS leaks and malware while encrypting data. Furthermore, the platform pioneers the SmartKPN mode, incentivizing users to contribute to the KonnektVPN ecosystem.

Read more
“AI Alone Cannot Save Disjointed Data Systems,” says Coginiti Founder

Artificial Intelligence has grabbed the attention of every business around the globe, driven by visions of automation and smarter decision-making. This has fueled a race to integrate AI into their operations. And yet, as per Gartner’s latest update, at least 30% of AI initiatives will be abandoned this year.
Why? “It’s not because AI doesn’t work,” states Rick Hall, founder of Coginiti. “It’s because most companies haven’t done the foundational work. They expect AI to clean up their mess, but it can’t. Companies need to clean up their own data before inviting AI in.”
 
Hall believes AI is still in the early phases of a decade-long transformation, one that will redefine nearly every business operation. But for that transformation to succeed, organizations must first tackle three persistent problems: poor alignment to business goals, bad data, and failed integration.
 
Companies often rush to implement AI without understanding how it will actually improve their business. “They start with the technology, not the outcome,” Hall states. “They can’t articulate what success looks like.” Without a clear hypothesis of what AI will do and the value it will drive, the initiative flounders.
 
Messy, redundant, and poorly labeled data is one of the most common obstacles to AI success. One of Coginiti’s clients, for example, had been using a cloud-based sales system for years. They wanted to deploy AI to optimize their sales pipeline. But their sales opportunity record had ballooned to 250 columns with four different fields just for purchase orders.
“Over time, processes change, people add fields, create nicknames, and now AI has no idea which one to use,” Hall explains. “You’re asking an algorithm to make sense of something even your sales team doesn’t fully understand.” Without clearly named, clean, and integrated data, no AI can deliver value.

Even when an AI model is successfully trained in a pilot program, many businesses struggle to scale it. That’s because they haven’t built clear bridges between their test environments and real-world operations. “You might have something that works in isolation, but integrating it into your existing systems, your workflows, your infrastructure, that’s where everything breaks down,” Hall says.
 
To solve these problems, Coginiti helps organizations build a digital twin, a virtual representation of how the business actually works. A digital twin isn’t just a model or a dashboard; it’s a semantic representation that maps your business processes, data, and systems in a structured, meaningful way.
 
“When you have a digital twin integrated into your system,” Hall says, “you can simulate change. You can say: ‘If we improve this process, we’ll see this benefit.’ It aligns your AI efforts to business value from the beginning.”
 
The digital twin acts as a translator between your messy, physical reality and a logical business model that AI can understand. It defines your data layer clearly and exposes it to AI tools in a way that is consistent and scalable.
 
A digital twin starts with understanding how your business actually runs. What are the key value chains? What are the metrics for improvement? This means data will be well-defined, consistently named, and logically organized. “The semantic model is the heart of a digital twin,” Hall says. “It’s what allows AI to interface with your business meaningfully.”
 
A true digital twin links clean, logical models to real-world data across systems: CRMs, ERPs, call centers, data warehouses, and more. A digital twin further pulls from across departments and platforms, ensuring a single, unified source of truth. With the integration in place, businesses can use AI agents to model changes, test new processes, and develop rapid pilots that can easily be deployed in production.
 
Ultimately, AI is not a magic bullet. It’s a powerful tool, but only as powerful as the foundation it rests on. “Think of AI as a new room in your house. If the blueprint is vague and the bricks are cracked, even the best architect can’t build a stable structure,” Hall compares. “The companies that invest in doing this the right way today will be tomorrow’s leaders.” Coginiti can help you with the transformation. 

Read more