Elevate your AI journey: From experimentation to production, MongoDB and Google Cloud can help your org accomplish its GenAI goals. Learn how.
AI’s potential is a no-brainer. But taking it from concept to production while controlling costs—and doing it in a way that keeps up in a rapidly evolving tech landscape—has turned out to be trickier than expected. According to a recent study by Boston Consulting Group, only 26% of companies have successfully moved beyond proofs of concept to achieve tangible results from their AI initiatives.
These challenges are forcing tech partners to move beyond the traditional approach. Providing the technology isn’t enough; vendors also need to support their customers at every stage of their AI journey. That means providing guidance on integrating AI into the tech stack, overcoming new technical challenges that come with it, and maintaining a forward-thinking view of this rapidly evolving tech. This new level of support is a foundational part of creating and sustaining AI confidence.
As a leading document database platform and the database built for AI applications, MongoDB is rising to the occasion in partnership with Google Cloud.
Together, MongoDB and Google Cloud have built integrations that offer the tools and expertise to support organizations, no matter where they are in their AI journeys. And we partnered with them to learn exactly what that end-to-end support looks like.
For enterprises
Enterprise orgs often struggle with speedy, confident AI implementation—hindered by tools that can’t scale and bolt-on solutions that add complexity and cost—and often just need help figuring out how to get started. So to help them build and deploy AI-powered applications rapidly, MongoDB partnered with an ecosystem of leading AI and tech companies, including Google Cloud, to create the MongoDB AI Applications Program (MAAP).
Think of MAAP as your one-stop solution to quickly and effectively embed GenAI into applications at scale. It provides strategic advisory, professional services, and an integrated end-to-end technology stack from MongoDB and founding MAAP partners like Google Cloud. Together, MongoDB and Google Cloud can help you identify business problems that can be solved with advanced AI-powered applications and build solutions with the required tech stack and expertise in place.
Through the MAAP program, enterprises get support taking advantage of MongoDB Atlas’s deep integrations with key Google Cloud generative AI platforms, including Vertex AI. It allows developers to quickly query, perform CRUD operations, and full text search directly on the data stored in MongoDB Atlas. You can even do so using natural language queries powered by Google Gemini, turning intuitive, human language into MongoDB-specific query syntax.
What’s more, MongoDB’s integration with Gemini Code Assist allows developers to seamlessly access the latest documentation and code snippets within their IDEs. That means less time hopping in and out of IDEs and more time staying ~ in the flow ~. The result of all of that? Developers can build applications more quickly, speed up time to value, and reduce friction along the way.
Curious what these capabilities look like in practice? Stax.ai, which is harnessing AI to rethink retirement plan administration, implemented a solution built with MongoDB Atlas on Google Cloud. Google Cloud enabled them to efficiently process tens of thousands of documents each day, while MongoDB Atlas provided flexible architecture that made it easy to manage diverse datasets. As a result, their processing times went from days to hours, and they were able to scale operations without additional infrastructure demands. By simplifying and automating manual workflows, Stax.ai’s retirement plan administrators can get back to serving clients, not spreadsheets.
For highly regulated industries
Adopting and scaling GenAI requires agile, flexible data infrastructure that can keep up with the unprecedented volumes of structured and unstructured real-time data. But many organizations are stuck on brittle, legacy databases that accumulate technical debt and are unable to evolve at the speed of today’s fast, AI-driven market.
Unfortunately, database migration has historically been a huge, expensive, and slow undertaking that comes with many risks. So for enterprises looking to make the leap to modern, AI-ready data infrastructure, it’s historically been quite a challenge.
MongoDB's modernization methodology helps companies overcome these challenges with a structured approach combining agentic AI orchestration, cutting-edge migration tools, and modern database capabilities, all enabled by a team of experienced engineers. This approach helps make it easier, faster, and more cost-effective to migrate legacy database environments to MongoDB Atlas on Google Cloud’s cloud infrastructure.
For Bendigo Bank, this framework helped reduce the development time required to migrate a core banking application off a legacy relationship database to MongoDB Atlas by up to 90%. But the real kicker? They modernized at one-tenth of the cost of a traditional legacy-to-cloud migration.
MongoDB and Google Cloud are also collaborating on new ways to further streamline the cloud modernization journey with Google Cloud Migration Center, a unified platform that streamlines the transition from on-premise servers to the Google Cloud environment. You can not only use it to generate cost assessments and migration plans, but also simplify the transition to MongoDB Atlas on Google Cloud. It all comes together to form the data infrastructure that’s capable of managing the amount of unstructured data that comes with GenAI.
For startups
Early-stage companies face a completely different set of AI adoption hurdles than enterprises, but typically, the goal is to build agile, intelligent apps that are capable of scaling into the enterprise level when the time comes.
To help these younger organizations, there’s Google Cloud and MongoDB for Startups. This program allows startups to leverage the combined power of MongoDB’s flexible, cloud-native database platform and Google Cloud’s comprehensive suite of cloud services (think machine learning tools, cost-effective storage, and more). Together, this duo removes the hassle of infrastructure management and allows startups to move faster with more agility.
With the MongoDB for Startups program, there’s dedicated onboarding support for MongoDB Atlas, plus hands-on training at MongoDB University. That means founders can get their AI solution in front of users and product teams and even have a one-on-one session with technical experts who will share personalized recommendations. And the cherry on top? Founders also get free credits for MongoDB products like Atlas Database and Atlas Vector Search that can supercharge their data infrastructure.
In the Google Cloud for Startups Program, founders access Google-wide discounts, training, and technical support. Plus, new AI benefits allow them to take advantage of Google’s AI ecosystem and tap into the best of their foundation models. And Web3 benefits help them focus more on innovation and less on infrastructure.
For everyone
As complex and fast-moving as the GenAI landscape can feel, MongoDB and Google Cloud are working together to make AI adoption incredibly straightforward. With the support of their deep integrations, tailored innovation programs, and professional services expertise, nimble startups and the largest enterprises alike can transform their pathway to AI readiness. Want to know what it feels like in practice? Partner with them and see for yourself.