Posted on mongodb google news. Visit mongodb google news

In an era where digital agility is no longer optional, Indian enterprises find themselves at a pivotal crossroad. With nearly 98% of enterprise applications still tethered to rigid, legacy systems, the challenge of modernization looms large—entangled in a web of technical debt, resistance to change, and the pressing demand for compliance in regulated sectors.

As India intensifies its push toward a digital-first economy, a cloud-agnostic approach is critical in transforming legacy roadblocks into scalable, AI-ready infrastructure. Boris Bialek, Field CTO at MongoDB, who brings global insight and deep technological expertise to the conversation on legacy modernization, shares with us how organizations can turn legacy challenges into launchpads for digital excellence.

Some edited excerpts:

What are the top challenges Indian enterprises face when modernizing legacy systems—be it technical debt, skill gaps, or resistance to change?
Modernizing legacy systems in India, or anywhere in the world, has historically been challenging, expensive and prone to stalling or complete failure. But one of the things we’re most excited about in 2025 is that our new AI-driven modernization process has proven it can dramatically accelerate the speed and reduce the cost of these projects.

But first, let’s look at what the challenges really are.

One of the primary obstacles enterprises face is, of course, technical debt. Outdated systems are deeply embedded in business operations, making migration complex, costly, and time-consuming. These legacy systems often have hardcoded dependencies and intricate architectures, necessitating substantial investment in re-engineering efforts.

Beyond technical debt, introducing new development processes and technologies across engineering teams remains a critical challenge. Organizations must ensure seamless adoption of AI-ready architectures while overcoming resistance to change. Legacy systems have often been in place for decades, and decision-makers fear disruptions to core operations, which slows down modernization efforts. Striking a balance between innovation and operational stability is crucial for enterprises undergoing transformation.

Given that 98% of enterprise applications in India still rely on legacy systems, how should Indian enterprises overcome the limitations of rigid relational databases, particularly in terms of scalability and innovation?

One of the most effective ways to overcome these challenges is by adopting a modern, document-based database like MongoDB. Unlike traditional RDBMS, MongoDB offers a flexible schema that allows organizations to evolve, adapt and scale. This adaptability is critical in today’s fast-paced business environment, where rapid iteration and responsiveness to market needs are key to staying competitive.

From a scalability perspective, MongoDB’s distributed architecture enables enterprises to scale horizontally, ensuring systems can handle growing workloads seamlessly—whether on-premises, in the cloud, or across hybrid environments. This is especially relevant for Indian enterprises expanding into digital-first services and real-time operations.

Moreover, MongoDB’s Application Modernization Factory (AMF) provides structured advisory and migration services, helping enterprises replatform legacy monolithic apps, rewrite core systems with modern tech stacks, and rehost databases on the cloud with MongoDB Atlas.

To move from a legacy infrastructure to a modern solution like MongoDB, enterprises must go on a modernization journey. As I mentioned earlier, AI is massively changing the dynamic of what’s possible in this area.

How is Generative AI reshaping the legacy modernization process for Indian enterprises, and what specific capabilities does MongoDB bring to the table to integrate GenAI into these transitions?
Generative AI is reshaping the legacy modernization process for Indian enterprises by streamlining application migration, reducing technical debt, and accelerating innovation. MongoDB plays a crucial role in this transformation by offering a cloud-agnostic, developer-friendly platform that integrates seamlessly with AI-driven modernization strategies. With tools like the MongoDB Modernization Factory, enterprises can migrate legacy SQL databases, transition from outdated application servers, and automate regression testing using GenAI. This significantly reduces the time and effort required for code migration, freeing up IT resources for more strategic AI-driven initiatives.

For Indian enterprises navigating large-scale modernization, MongoDB’s scalable and AI-ready architecture ensures flexibility, improved developer productivity, and compliance with regulatory requirements.

With India’s digital transformation accelerating, what is MongoDB’s strategy to capture the growing market opportunity for legacy modernization, particularly among PSUs and traditional enterprises?
For the Indian market—particularly public sector undertakings and traditional enterprises—our goal is customer focused. We want to make modernization faster, more cost-effective, and scalable—unlocking innovation and delivering better citizen and customer experiences.

Depending on the customer or the exact use case we have a number of proven methods for modernizing. More recently, we’ve combined these with the power of Generative AI to accelerate the modernization journey—intelligently assisting in rewriting legacy code, redesigning database schemas, and streamlining application migration.

As AI evolves, we foresee even more intuitive tools that will make application development and modernization easier than ever—turning India’s legacy burden into a leapfrog opportunity.

Beyond modernization, MongoDB is trusted by some of India’s most dynamic businesses and institutions. Our customer base includes names like Canara HSBC, Zepto, Zomato, and SonyLIV—reflecting the platform’s flexibility, scale, and performance across diverse use cases.

Article originally posted on mongodb google news. Visit mongodb google news