Reflections On Our Recent AI "Think-A-Thon"

Veronica Cooley-Perry
October 23, 2024
#genAI

Interesting ideas are bound to emerge when great minds come together, so there was no shortage of interesting ideas on October 2nd, when MongoDB’s Developer Relations team hosted our second-ever AI Build Together event at MongoDB.local London.

In some ways, the event is similar to a hackathon: a group of developers come together to solve a problem. But in other ways, the event is quite different. While hackathons normally take an entire day and involve intensive coding, the AI Build Together events are organized to take place over just a few hours and don't involve any coding at all. Instead, it’s all based around discussion and ideation. For these reasons, MongoDB’s Developer Relations team likes to dub them “think-a-thons.”

Our first AI Build Together event was held earlier this year at .local NYC. After seeing the energy in the room and the excitement from attendees, our Developer Relations team knew it wanted to host another one.

The .local London event’s fifty attendees—which included developers from numerous industries and leading AI innovators who served as mentors—came together to brainstorm and discuss AI-based solutions to common industry problems.

Photo of .local London AI Build Together attendees brainstorming AI solutions for the healthcare industry. The group is sitting around a table and writing down ideas on a giant notepad. The room is filled with more tables of other groups doing the same thing. — .local London AI Build Together attendees brainstorming AI solutions for the healthcare industry

The AI mentors included: Loghman Zadeh (gravity9), Ben Gutkovich (Superlinked), Jesse Martin (Hasura), Marlene Mhangami (Microsoft), Igor Alekseev (AWS), and John Willis and Patrick Debois (co-founders of DevOps).

Upon arrival, participants joined a workflow group best aligned with their industry and/or area of interest—AI for Education, AI for DevOps, AI for Healthcare, AI for Optimizing Travel, AI for Supply Chain, and AI for Productivity.

Photo of the AI for Productivity group collaborating on their workflow. The group is siting around a table and writing down ideas on a giant notepad. — The AI for Productivity group collaborating on their workflow

The discussions were lively, and it was amazing to see how much energy these attendees brought to their discussions.

For example, the AI for Education workflow group vigorously discussed developing a personalized AI education coach to help students develop their educational plans and support them with career advice.

Meanwhile, the AI for Healthcare workflow group focused on the idea of creating an AI drive tool to provide personalized healthcare to patients and real-time insights to their providers.

The AI for Productivity team came up with a clever product that helps you read, digest, and identify the key aspects of long legal documents.

The AI for Optimizing Travel group seeking advice from AI mentor Marlene. The group is at a table discussing what the team had written down on the notepad. — The AI for Optimizing Travel group seeking advice from AI mentor Marlene

A talented artist was also brought in to visualize each workflow group’s problem statements and potential solutions—literally and figuratively illustrating their innovative ideas.

Photograph of graphic recorder Maria Foulquie putting the final touches on an illustration. She is kneeling on the ground drawing on a big board with a crowd around her watching. — Graphic recorder Maria Foulquié putting the final touches on the illustration

Final illustration documenting the 2024 MongoDB.local London AI Build Together event

All in all, our second time hosting this event was deemed a success by everyone involved.

“It was impressive to see how attendees, regardless of their technical background, found ways to contribute to complex AI solutions,” says Loghman Zadeh, AI Director at gravity9, who served as one of the event’s advisors. “Engaging with so many creative and forward-thinking individuals, all eager to push the boundaries of AI innovation was refreshing. The collaborative atmosphere fostered dynamic discussions and allowed participants to explore new ideas in a supportive environment.”

If you’re interested in taking part in events like these—which offer a range of networking opportunities—there are three more MongoDB.local events slated for 2024—Sao Paulo, Paris, and Stockholm. Additionally, you can join your local MongoDB user group to learn from and connect with other MongoDB developers in your area.

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Gamuda Puts AI in Construction with MongoDB Atlas

Gamuda Berhad is a leading Malaysian engineering and construction company with operations across the world, including in Australia, Taiwan, Singapore, Vietnam, the United Kingdom, and more. The company is known for its innovative approach to construction through the use of cutting-edge technology. Speaking at MongoDB.local Kuala Lumpur in August 2024 , John Lim, Chief Digital Officer at Gamuda said: “In the construction industry, AI is increasingly being used to analyze vast amounts of data, from sensor readings on construction equipment to environmental data that impacts project timelines.” One of Gamuda’s priorities is determining how AI and other tools can impact the company’s methods for building large projects across the world. For that, the Gamuda team needed the right infrastructure, with a database equipped to handle the demands of modern AI-driven applications. MongoDB Atlas fulfilled all the requirements and enabled Gamuda to deliver on its AI-driven goals. Why Gamuda chose MongoDB Atlas “Before MongoDB, we were dealing with a lot of different databases and we were struggling to do even simple things such as full-text search,” said Lim. “How can we have a tool that's developer-friendly, helps us scale across the world, and at the same time helps us to build really cool AI use cases, where we're not thinking about the infrastructure or worrying too much about how things work but are able to just focus on the use case?” After some initial conversations with MongoDB, Lim’s team saw that MongoDB Atlas could help it streamline its technology stack, which was becoming very complex and time consuming to manage. MongoDB Atlas provided the optimal balance between ease of use and powerful functionality, enabling the company to focus on innovation rather than database administration. “I think the advantage that we see is really the speed to market. We are able to build something quickly. We are fast to meet the requirements to push something out,” said Lim. Chi Keen Tan, Senior Software Engineer at Gamuda, added, “The team was able to use a lot of developer tools like MongoDB Compass , and we were quite amazed by what we can do. This [ability to search the items within the database easily] is just something that’s missing from other technologies.” Being able to operate MongoDB on Google Cloud was also a key selling point for Gamuda: “We were able to start on MongoDB without any friction of having to deal with a lot of contractual problems and billing and setting all of that up,” said Lim. How MongoDB is powering more AI use cases Gamuda uses MongoDB Atlas and functionalities such as Atlas Search and Vector Search to bring a number of AI use cases to life. This includes work implemented on Gamuda’s Bot Unify platform, which Gamuda built in-house using MongoDB Atlas as the database. By using documents stored in SharePoint and other systems, this platform helps users write tenders quicker, find out about employee benefits more easily, or discover ways to improve design briefs. “It’s quite incredible. We have about 87 different bots now that people across the company have developed,” Lim said. Additionally, the team has developed Gamuda Digital Operating System (GDOS), which can optimize various aspects of construction, such as predictive maintenance, resource allocation, and quality control. MongoDB’s ability to handle large volumes of data in real-time is crucial for these applications, enabling Gamuda to make data-driven decisions that improve efficiency and reduce costs. Specifically, MongoDB Atlas Vector Search enables Gamuda’s AI models to quickly and accurately retrieve relevant data, improving the speed and accuracy of decision-making. It also helps the Gamuda team find patterns and correlations in the data that might otherwise go unnoticed. Gamuda’s journey with MongoDB Atlas is just beginning as the company continues to explore new ways to integrate technology into its operations and expand to other markets. To learn more and get started with MongoDB Vector Search, visit our Vector Search Quick Start page.

October 22, 2024

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MongoDB Named a Leader in the 2024 Gartner® Magic Quadrant™ for Cloud Database Management Systems

I’m pleased to announce that MongoDB has been named a Leader in the 2024 Gartner® Magic Quadrant™ for Cloud Database Management Systems (DBMSs) for the third consecutive year. In our view, this recognition cements MongoDB’s status as the only pure-play database provider in the cloud database management system category, underscoring MongoDB’s innovation, execution, and customer-centric approach. According to Gartner, “The cloud DBMS market remains as vibrant as ever and is transforming in important ways, especially in the use of gen AI and how DBMSs interact with other data management components. This Magic Quadrant will help data and analytics leaders make the right cloud DBMS choices in this essential market.” We believe this continued recognition by Gartner is a testament to MongoDB’s commitment to serving developers, as well as the investments we’ve made in our unified platform and integrated services. Driving innovation for enterprises MongoDB's mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. 2024 was a year of innovation and accolades at MongoDB, and I’m proud to share some of its highlights: In October, we released MongoDB 8.0 , the best performing version of MongoDB yet. MongoDB 8.0 is over 30% faster than the previous version of the database, it’s more secure than ever, horizontal scaling is faster and easier (at a lower cost), and MongoDB 8.0 gives teams greater control for optimizing database performance. We also launched—and grew—the MongoDB AI Applications Program (MAAP) . With MAAP, MongoDB offers customers a full AI stack and an integrated set of professional services to help them keep pace with innovation, identify the best AI use cases, and to help them future-proof AI investments. MongoDB became a founding member of the U.S. Artificial Intelligence Safety Institute Consortium . Established by the U.S. Department of Commerce’s National Institute of Standards and Technology, the Consortium supports the development and deployment of safe and trustworthy AI. MongoDB released hundreds of features and enhancements to accelerate innovation, manage costs, and simplify building applications at scale. MongoDB was recognized as the most loved vector database in Retool’s State of AI report —for the second consecutive year. The Gartner Magic Quadrant for cloud database management systems “Gartner defines the cloud database management systems (DBMSs) market as solutions designed to store, manipulate, and persist data, primarily delivered as Software-as-a-Service (SaaS). These systems must support transactional, analytical, and hybrid workloads while enabling enterprises to innovate across multi-cloud, hybrid, and intercloud ecosystems.” 1 It’s our opinion that this recognition by Gartner is a testament to MongoDB’s strong ability to execute and support customers today, as well as MongoDB’s comprehensive product vision that positions our platform to support tomorrow's operational workloads. What is the Magic Quadrant, and what is a Leader? “A Gartner Magic Quadrant is a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market’s competitors. By applying a graphical treatment and a uniform set of evaluation criteria, a Magic Quadrant helps you quickly ascertain how well technology providers are executing their stated visions and how well they are performing against Gartner’s market view.” 2 According to Gartner, “Leaders execute well against their current vision and are well positioned for tomorrow.” Overall, Magic Quadrants can help you “get quickly educated about a market’s competing technology providers and their ability to deliver on what end-users require now and in the future.” Powering innovation at scale with MongoDB Atlas Enterprises choose MongoDB Atlas because it gives them the freedom and agility they need to succeed in a rapidly evolving digital landscape. MongoDB Atlas’s multi-cloud architecture—including availability across Amazon Web Services, Google Cloud, and Microsoft Azure—ensures customers can design for unmatched scale and resilience. By automating functions like scaling and performance optimization , and giving them the ability to leverage industry-first capabilities like MongoDB Queryable Encryption (which allows customers to encrypt, store, and perform queries directly on data), with MongoDB Atlas customers can spend less time managing infrastructure and more time delivering experiences. MongoDB Atlas’s integrated capabilities to support multi-modal data types and use cases—like full-text and vector search , stream processing , and data federation —accelerate innovation, helping enterprises quickly respond to market changes, power AI-driven insights, and deliver meaningful digital experiences to their end users—all without the burden of operational complexity. Modernizing and building for the future In our opinion, the Gartner Magic Quadrant provides organizations with a clear and accessible evaluation framework to identify solutions that fit their needs, today and tomorrow. The placement of MongoDB in the Leader quadrant for Cloud Database Management Systems—for the third year in a row!—validates the efforts MongoDB has made to help developers and organizations take advantage of their most valuable resource, their data. I talk to MongoDB customers frequently, and many say the same thing: in today’s digital-first economy, AI-powered applications and scalable data infrastructure aren’t just advantages, they’re absolute necessities. They say that the time to act is now, and they’re looking for solutions that will help them innovate, streamline, and seize the AI-driven future. And when it comes to modernizing their operations, they consistently point to MongoDB as their go-to partner. Begin your cloud journey with MongoDB Atlas today. Contact our sales team or register for a free account to begin building! And to learn how MongoDB can help accelerate your AI journey, visit the MongoDB AI Applications Program page. Footnotes Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Ramke Ramakrishnan, et al., 18 December 2024 GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. 1 Gartner Peer Insights, Cloud Database Management Systems, December 2024 https://www.gartner.com/reviews/market/cloud-database-management-systems 2 Gartner Research Methodologies, Gartner Magic Quadrant, 20 December 2024 https://www.gartner.com/en/research/methodologies/magic-quadrants-research

December 23, 2024