Circles Uses MongoDB to Fuel Jetpac’s Rapid Global Expansion

Founded in Singapore in 2014, Circles has grown to become a global telecommunication company revolutionizing the industry with its cutting-edge SaaS platform. Present in 14 countries, Circles empowers telco operators worldwide to launch innovative digital brands and refresh existing ones, accelerating their transformation into 'techcos'.

MongoDB Atlas is at the heart of Circles' success, enabling one of Circles' biggest product launches, Jetpac, in 2022.

Kelvin Chua, Head of Markets, and Circles' first employee, described Circles' experience at the recent MongoDB .local Singapore, in July 2025. During a Fireside session, Chua shared insights into Circles' journey and his own close relationship with MongoDB.

Here's the full conversation.

Before we dive into your work with MongoDB, could you please introduce yourself?

Sure. I am currently the Head of Markets for Circles, but I am also their first employee.

I've been working in the telco space for more than 20 years, and I've been around the ecosystem of startups a lot, helping build and scale startups. Actually, the first time I used MongoDB was for a startup in the [Silicon] Valley.

So you have a pretty long standing relationship with MongoDB. Can you tell us a bit more about that?

As I said, my relationship with MongoDB dates back to my start-up days, when MongoDB was still in its infancy.

I chose MongoDB to handle about 5 million documents per hour. That was back in 2013. From there, I started looking at how MongoDB scales.

Years later, I continued to leverage MongoDB to help build Circles in Singapore, but also for scaling the company globally across Pakistan, Mexico, and other regions.

How [did] Circles' journey with MongoDB start?

Circles was built on the Community Edition of MongoDB back in 2014. At the time, our team was using Node.js, and I immediately knew that MongoDB and a NoSQL database model was the right choice to build and scale the business.

As a fan of Node.js, it was very natural to feel the ease of using MongoDB. I feel like using Node.js for your workload and then using MongoDB for the backend creates the best tandem.

As we transitioned to other development environments and languages, including Golang, MongoDB remained at the core of our database operations, mostly because of its flexibility, the ease of prototyping, and the scalability.

We never really saw the need to change from MongoDB as our requirements for a document store are always fulfilled by it.

More recently, Circles launched a very successful offering: Jetpac. … This was also built on MongoD, but before we dive into this, can you share more about what sparked the idea for this product?

As you know, the COVID-19 pandemic put a hold on all international travel. So when 2022 rolled in, we were expecting a boom in travel again as restrictions eased up. This is when we had the idea for Jetpac, which is basically a travel tech solution providing seamless roaming and innovative travel lifestyle products.

You had a pretty challenging timeline to work against, though?

Yes! We had a massive challenge because we had six weeks to build Jetpac right from zero. That included solutioning, strategizing, and team-building.

Having had ten years of experience working with MongoDB, I knew we needed a NoSQL database, especially to keep track of what people are buying, how they are using the packs, and how to present usage to customers.

So Jetpac was built on MongoDB Atlas in just six weeks, in time to launch before the end of year holiday period where international travel was expected to resume.

Since then, Jetpac expanded really quickly: revenue grew 500% between January and November 2024, and it is now available in 200 countries. Jetpac is not just a Singapore product anymore-it's a global brand.

Can you explain why you recently decided to move from MongoDB Community to Atlas for your operations in Singapore?

Sure. After several years running and scaling the business on MongoDB Community Edition, we decided that it was time to move to MongoDB Atlas because we wanted to optimize efficiencies and reduce operational costs across Circles' markets, as well as reduce and ease the regulatory compliance risk and burden posed by the Singapore telco industry.

It all started when we decided to run an internal comparison to look into how many resources were spent on maintaining our database internally, versus moving to MongoDB Atlas.

We realized that we were running very inefficient clusters-many clusters with only about 10% utilization per cluster. That cost goes to the cloud provider. We found that we could aggregate these clusters into MongoDB Atlas to improve utilization and save money.

Another main benefit of moving to MongoDB Atlas was the flexibility and productivity that this offered our engineering and developer team.

That is something we hear a lot from our customers, how MongoDB Atlas really helps empower their engineering team. How did that show up for you and your team?

MongoDB Atlas amplifies everything very fast. It allows engineers to make mistakes in sandbox environments in a way where they don't get constrained by wondering, 'What can I break?' If they make a mistake, they can spin up a new instance and move forward. That is really valuable.

Also, with automation and workflows streamlined under MongoDB Atlas, we have really been able to expedite new projects.

For example, I was in India a few weeks ago for one of our new Jetpac B2B projects. We were able to shortcut our process by about a week just because contractors could access MongoDB Atlas and select schemas immediately-no delays in consulting environments!

What does the future hold for Circles? What are your priorities? What technologies are you investing in?

I think AI is really a big priority for us. Actually, some of our users might already have noticed that our app is starting to evolve into a more AI-powered application- we provide predictions, automatic waivers, personalized special offers, and more.

As a company, Circles plans to continue leveraging MongoDB as we scale these AI operations, particularly for retrieval-augmented generation (RAG) projects where we want to rely on MongoDB's vector search capabilities.

I love hearing that and am really looking forward to seeing all of these projects come to life! Thank you so much for being with us, Kelvin.

Thank you.