Since I joined MongoDB in March, it’s become clear that people build on MongoDB because they trust it to power what matters most.
That conviction has become even clearer as we’ve marked MongoDB Atlas’s tenth anniversary, looking back at what customers have built and all they’ve accomplished.
When we’ve asked customers “Why Atlas?” over the years, the answer has always been the same: they want technology that helps them move faster, adapt to change, and build with confidence. They want to move quickly on AI, work with complex and fast-changing data, and stay flexible as business and regulatory demands evolve.
And with Atlas, that’s exactly what they’ve done.
That is what makes this anniversary so meaningful. Atlas’s story has never been about the evolution of a cloud database alone – it’s about the ambition customers bring to the platform and the outcomes they achieve.
And the best way to tell that story is to hear directly from them.
10 years of customer success stories
Perhaps the best part of my job as CCO is talking to our customers – hearing their stories, helping to solve their struggles, and celebrating their successes.
Like Amadeus, a travel software provider that serves one million transactions per second for 170 airlines globally, built iPIM, an intelligent incident investigation tool, using MongoDB Atlas Search, Atlas Vector Search, and OpenAI to match new issues to historical context across unstructured data. Now, with a consolidated, secure stack, Amadeus teams can detect bugs and resolve issues in minutes.
Marsh, a Fortune 500 insurance giant, learned early that flexibility matters more now than ever. Its AI platform, Lenai, initially struggled because developers had to start from scratch for each interaction. By using MongoDB’s flexible schema with semantic and hybrid search, Marsh added a persistent memory layer that can pinpoint exact structured information, like policy numbers, while still understanding the intent behind an employee’s question. Today, Lenai has an 89% adoption rate across Marsh’s 90,000 employees and saves them roughly 100 hours per colleague, per year.
Toyota Connected North America, an independent Toyota company focused on advanced software engineering, AI, machine learning, and data science in the mobility space, is a strong study of why deployment freedom matters. More than 20 Atlas databases power the telematics platform behind Toyota’s Safety Connect service suite, which Toyota has measured attained 99.99% availability, helping support emergency services for more than 9 million Toyota and Lexus vehicles. Atlas’s multiregional capabilities also let the team run maintenance and upgrades without downtime.
Networking and cybersecurity giant Cisco needed to roll out hundreds of AI applications while maintaining strict security standards. MongoDB quickly achieved the security certifications required by Cisco, helping the company create secure Atlas sandbox clusters for experimentation. On top of that foundation, Cisco used MongoDB Atlas Vector Search on Atlas to power RAG for its Webex virtual assistant, semantically indexing 3,600 help articles. That assistant has deflected or resolved more than 100 support cases and saved Cisco roughly $10 million.
Built for what’s next
The stories are strong, but they point to a larger trend. Atlas continues to expand alongside customer ambition, from a simpler way to run MongoDB in the cloud to a unified data platform built around what builders need most: flexibility, scale, and reduced operational overhead.
Success with AI will not come from stitching together a mess of disconnected systems and hoping for the best. It’s through a single platform that supports operational data, search, and retrieval while remaining secure, scalable, and ready for production.
That difference is why I came to MongoDB, and why I’m excited for what’s ahead. You’ve trusted Atlas for a decade, together we’ve proven what’s possible, and now we get to define what’s next.
Next Steps
Ready to build? Get started with MongoDB Atlas today.