We aim to enable users to focus less on data structures & more on content: Boris Bialek, Field CTO, MongoDB  

The rise of generative artificial intelligence (Gen AI) is changing how we use databases. MongoDB's NoSQL database system seeks to empower businesses to efficiently manage and utilise their data. The company believes that Gen AI offers exciting possibilities for enhancing its capabilities and shaping the future of data management. In an interview with TechCircle, Boris Bialek, Field CTO of Industry Solutions at MongoDB, delved into the integration of Gen AI and its impact on platforms like MongoDB. Edited Excerpts:  
  
Can you provide insights into MongoDB’s current presence and operations in India? 

So, looking at the big picture, things are pretty exciting. Our organisation, based in Delhi, is quite expansive. We've got everything you'd find in any major hub: support services, sales, pre-sales, and a whole lot of operations. Take my Early Access Program team, for instance, responsible for global access to unreleased software — we're based right here in Gurugram. We've been helping people all across India, providing technical support and services. We've established official locations across India and have garnered business from thousands of clients. Our team has experienced remarkable growth, making India one of our fastest-growing areas. 
 
What are MongoDB's strategies for expansion and growth within the Indian market? 

The interest in our keyboard is growing, especially among developers. Many clients start with MongoDB's community version but eventually seek more professional services. They come to us for various reasons, such as needing better service availability. We discuss their needs and offer assistance where we can add value. We don't pressure clients to switch from the community version if it meets their needs. However, when they're ready for commercial products, we're there to help them transition. We assist in migrating from legacy infrastructures to modern, document-driven applications. 

It's essential to understand that MongoDB isn't just a database; it's part of our developer data platform. Alongside the core database, we offer features like vector search, crucial for AI applications, and full-text search integration, commonly used in e-commerce and banking. We also integrate with mobile platforms, aiming to provide developers and clients with a comprehensive, easy-to-use solution for their data needs, minimising the use of multiple platforms. 

In today's cloud environment, managing multiple database scenarios can be cumbersome. MongoDB Atlas offers a streamlined solution, reducing overhead and providing tighter integration, whether on-premises or in the cloud.

Could you share any upcoming initiatives or plans MongoDB has for its business in India?

We're heavily invested in fostering innovation and developer communities in the Indian market. Our AI Innovators Program specifically targets startups, particularly digital natives, to help them build cutting-edge AI applications. We recently hosted a successful roundtable with CTOs from Bangalore startups, demonstrating our commitment to this space. 

Furthermore, we prioritise educating both current and potential clients on how to utilise AI technologies effectively. We achieve this through various initiatives, including educational resources on university.mongodb.com, where we collaborate with leading universities. 

However, our focus extends beyond general education. We recognise the specific needs of the Indian market and actively work with vendors to deliver customised solutions that cater directly to Indian businesses. This commitment was further emphasized by a recent productive discussion focused on building better solutions for India within India. 

Finally, we understand the importance of developer communities. We host events like MongoDB Days and meetups to foster a strong network where developers can share knowledge and expertise. This focus on developers aligns with our core belief — "software will build the future, and developers will build it". Our ongoing collaboration with various developer communities throughout India demonstrates this philosophy in action.

Can you elaborate on the transformative impact of AI's vector search technology on cyberspace and digital landscapes? 

Today, when AI is discussed, the focus is on Gen AI, also known as RAG. But let's simplify things. Instead of diving into technical jargon, let's consider the core concept: Large Language Models (LLMs). Many LLMs are becoming proprietary, like the ones specific to certain companies. For instance, imagine a manufacturing giant with sensitive data that prefers keeping it offline. That's where proprietary LLMs come in, powered by custom chips.  

Now, let's talk about handling the data. LLM data is stored and processed using vectors, efficiently managed by tools like MongoDB. These vectors are crucial for tasks like summarising articles in real-time or gathering insights for financial analysis. By combining fresh data with industry models, we enhance the accuracy of AI-powered tasks. 

So, how does it work in practice? Picture a media professional needing quick insights for an upcoming interview. They don't want to deal with programming vectors; they need a user-friendly application. That's where MongoDB's vector search functions shine. They provide fast and efficient access to relevant information, eliminating the need for multiple tools and environments. 

This approach is particularly appealing to startups and digital natives. With just three clicks, they can integrate cutting-edge AI capabilities into their applications. This seamless integration sets us apart, allowing us to collaborate closely with innovators in the digital space. In essence, the vector search acts as a bridge between complex LLMs and practical data applications. It's the key to unlocking the full potential of AI in various industries.

How do you see the integration of Gen AI impacting the development and usage of data platforms like MongoDB? 

It's truly remarkable! We're bridging two sides here: aiding user communities to develop faster and more elegantly. Take for instance the work we're doing with Amazon's code whisperer. Developers are getting a major speed boost. Let me introduce you to Compass, a tool that simplifies complex tasks. Just input plain text, and voila! It generates code like a pro. You can customise it effortlessly too. This not only saves a ton of time but also enhances transparency and trust. 

With MongoDB Atlas, everything is encrypted and visible, making data management a breeze. This transparency is key, especially when it comes to sensitive data. I recently worked with a European automotive giant. In just four hours, we had a cutting-edge solution up and running, thanks to MongoDB's simplicity and power. 

Now, let's talk about the real impact. Imagine making decisions based on behavioural patterns or detecting fraud instantly. With our technology, it's possible. Clients are embracing these capabilities wholeheartedly, moving from experimentation to full-blown AI applications in record time. It's a game-changer, unlike the hype surrounding other technologies like blockchain. 

In fact, according to a recent study, over 26% of companies aim to have AI applications in production this year. That's not just talk; it's real progress shaping the future of industries, from banking to beyond.

Could you provide insights into MongoDB's approach to tech investment and innovation, especially given the increasing demand for advanced data management solutions?

Our investment focuses on improving data usability with over 1,000 people dedicated to research and development on a single product. This concentration is significant compared to others in the market. We're rapidly generating innovations and delivering software updates every three months, a stark contrast to the slower release cycles of the past. Clients appreciate this agility, which is why MongoDB is their preferred choice. 
 
What areas or technologies is MongoDB currently investing in to drive innovation and maintain its competitive edge in the market?

The AI revolution is just kicking off, with heavy investments pouring in to improve vector search and string technologies. Our Atlas Streams are already making waves, designed for real-time operations which are increasingly crucial. Gone are the days of ponderous big data warehouses; now, real-time decision-making reigns supreme. We're empowering developers to wield this power effectively. Our focus is clear: real-time processing, lightning-fast data handling, and seamless scalability.

Last year, we showcased our prowess by handling a staggering 150,000 banking transactions in record time. This year, we're set to push boundaries even further. Our goal is to simplify systems, allowing users to focus less on data structures and more on content. Major releases are becoming an annual tradition, with version eight on the horizon. We're also expanding our reach, ensuring our services are available wherever our users need them. Multi-cloud capabilities are a priority, ensuring a consistent MongoDB Atlas experience across different platforms and regions. Whether it's Google, Azure, AWS, or others, we've got you covered. Our commitment to innovation and accessibility drives us forward, with ongoing investments to shape the future of AI and cloud computing.