As companies move from AI experimentation to production, Gustavo Loewe explains how MongoDB is providing the flexible data platform needed for success
Freedom to run data anywhere
Gustavo Loewe, SVP EMEA at MongoDB
MongoDB was founded in 2007 to fix what legacy databases got wrong. Its modern data platform is built around a document model that mirrors how builders think and code – flexible, performant and unconstrained by rigid structures.
Today, it powers some of the world’ s most complex workloads, including next-generation AI applications.
In sectors like financial services and insurance, regulatory pressure means that where data sits is every bit as important as how it performs. Security, compliance and data sovereignty are non-negotiable.
“ Customers need choice in how and where their data runs,” Gustavo continues.“ With MongoDB, organisations can deploy across different cloud providers, place data in specific regions to meet regulatory requirements or keep systems on-prem when compliance demands it. If data needs to remain in a particular country, we support that.
Turning complex data into production-ready AI
Most businesses are under intense pressure to integrate AI into their operations, but many are hampered by data trapped in siloed and often legacy systems. It is a challenge MongoDB was built to solve
Gustavo Loewe, SVP EMEA at MongoDB, says enterprises are increasingly hitting these issues headon:“ Data is messy, architectures become complex and, once systems are in production, the stakes are high. That’ s exactly where MongoDB comes in.
“ Databases have underpinned the software stack for more than 60 years and MongoDB is the modern platform for the AI era, freeing teams from juggling multiple systems so they can build, ship and scale faster. Today, we power mission-critical workloads for at least 62,500 customers across more than 125 cloud regions.”
A clear example is DEX provider Nexthink, which helps enterprises monitor and improve the digital experience of their employees. After migrating to MongoDB, the company eliminated outages, cut latency by 98 % and now uses a single platform to power both operational data and AI agents that resolve technical issues proactively.“ Nexthink can innovate faster using one platform for both operational data and AI,” says Gustavo.
“ That same flexibility builds resilience. Businesses can’ t afford downtime, so MongoDB allows customers to distribute data across regions or span multiple cloud providers, ensuring uptime and availability while reducing risk. The goal is to give customers the freedom to run their data anywhere that makes most sense, without compromising on security, compliance or reliability.”
From AI pilots to production
As organisations move beyond early experiments, the real challenge is building systems that operate reliably at scale. The companies succeeding are those simplifying their data foundations rather than adding complexity.
“ The winners are the ones trying to simplify,” adds Gustavo.“ They treat data as a core product, getting the right information at the right time from their own systems, which makes it relevant for AI decision-making.”
As AI adoption accelerates, the organisations that pull ahead will be those that turn complex data into reliable systems powering real decisions.
The platforms that simplify how data is stored, accessed and operationalised will be the ones that help businesses move AI from promising pilots to everyday infrastructure. MongoDB is at the forefront.