MongoDB’s Quiet Dominance in India’s AI Boom
With the new wave of building AI-powered applications, new technologies have emerged that help companies operate more efficiently while keeping pace with rapid changes. From quick-commerce players like Zepto to sovereign funds seeking to modernise infrastructure, MongoDB is showing up in use cases that range from ESG compliance to semantic search. It’s not always front and centre, but it is usually underneath. In an exclusive interaction with AIM, explaining the role of MongoDB in the AI era, Sachin Chawla, VP, India & ASEAN of MongoDB, said, “There is no doubt that AI can play a role. At the same time, the reality is that we are probably at the start of this whole revolution.” A New Stack for New-Gen Applications For Chawla, the current wave of generative AI resembles the dawn of the computing era. “The way I think of AI is, think of it like an operating system. If you go back to 1960 [to compare with] LLMs, it is like an operating system [on top of] which people will now start building apps.” The earliest examples, he noted, were naturally rudimentary. Chatbots, summarisation, and basic assistants. But MongoDB expects far more complex applications to follow as the ecosystem matures. “Cursor, which is the most used tool for coding, is an app built using MongoDB,” Chawla pointed out. It’s not just about storage any more. From vector search and full-text indexing to embedding models, MongoDB is evolving into a comprehensive platform for AI development. He said MongoDB stands out when considering an application’s data demands, especially for AI applications. It excels in managing the sheer volume, scalability, speed, and performance required, particularly given that AI data is predominantly unstructured, which necessitates storage in a document data format. “So, I think that is where MongoDB has an edge”, he said. India’s AI Leap, Without the Mainframe Baggage While companies around the world struggle with deeply entrenched legacy systems, Indian enterprises are skipping a generation. When asked about his thoughts on how Indian tech companies differ in terms of upgrading legacy systems, he said, “I would say in a way it is a little better in India because we don’t have mainframes.” Chawla continued, “India leapfrogged, and you still see some of the large companies outside will still have mainframes running monolithic applications.” That doesn’t mean India lacks complexity. He noted that there are still monolithic applications in use, but with the help of modernisation frameworks and AI-native features, MongoDB is assisting Indian companies in closing the gap and making significant progress. “We are very thrilled about this whole modernisation approach using AI, [like] the one that is happening with IntellectAI. And I think more and more companies that have legacy applications will use this approach because this makes them go faster and take the risk,” Chawla said. He also shared an example of Tata Digital, where its Tata Neu super app unites 40 brands under one loyalty programme, built from the ground up on MongoDB. Startups, Sovereign Funds, and Streaming Giants The adoption is widespread, from startups to media giants. “We have a small NBFC, which is Capri Global, which uses vectorisation to make decisions on whom to give loans in different parts of the country,” said Chawla. Content streaming platforms are also making the shift. “SonyLiv is another example. Their CMS platform uses MongoDB. Again, they saw almost 98% performance improvement when they moved from their legacy app to us,” Chawla said. Hindustan Times, with over 270 million monthly users, also rebuilt its content management system on MongoDB. Even insurance providers are jumping on board. “Canara HSBC Insurance, Tata AIG, a lot of large enterprises, as well as startups, as well as ISVs, as you can see, use us.” And then there’s Zomato. “Zomato uses MongoDB for auto-tracking, assignment, and even partner onboarding,” said Chawla. A Platform, Not Just a Database MongoDB’s real play lies in its full-stack approach to AI data infrastructure. “We are storing the operational data in MongoDB, you have full-text search, so you do not need another engine like Elastic.” The company provides vector search embedded, which means one does not need another database like Pinecone. Additionally, the company acquired Voyage AI for embedding models. This native integration is what makes MongoDB increasingly attractive to developers and architects looking to avoid the heavy lifting associated with handling data from AI-driven applications. Instead, the platform offers a clean, all-in-one foundation. “In our case, everything is integrated now,” Chawla added. “We are the natural home to store in [document data format], you cannot store them in a table and row format.” India Is a Hotspot For Everything MongoDB With 700 employees in India and a new engineering team launched this year, MongoDB is making a significant investment in the region. When asked if he thinks MongoDB is India’s favourite tech platform right now? “I would say we are very kind of omnipresent,” Chawla said. “If you go from somebody trying to develop something to an enterprise, a lot of the new-age applications are built on MongoDB.” The company is also investing at the grassroots. Its training initiative, run in partnership with AICTE, GeeksforGeeks and other platforms, has already trained over 200,000 Indian students, with a goal of reaching half a million. He also said they host Developer Days (meetups) in various cities to showcase upcoming MongoDB features, new solutions, and customer success stories. They also conduct design reviews for specific use cases and hold meetups to discuss industry-specific solutions. A dedicated community team builds and nurtures the MongoDB user community. “There’s a lot of effort on developing skills at the ground level — tying up with universities, training the trainer, university professors, and so on,” Chawla said.
MongoDB is an increasingly popular choice among tech companies in India. Why is that the case?
MongoDB is an increasingly popular choice among tech companies in India. Why is that the case?
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["AI", "generative AI", "Aim", "RAG", "Pinecone", "chatbots", "semantic search", "MongoDB", "R", "Go"]
I am a tech aficionado and a computer science graduate with a keen interest in AI, Coding, Open Source, and Cloud. Have a tip? Reach out to ankush.das@aimmediahouse.com