As artificial intelligence reshapes industries, AI database integration has become a cornerstone for connecting advanced AI capabilities with practical, real-world applications.

Innovations in this space empower developers to simplify data usability and scalability, most notably in AI-driven projects.

MongoDB’s Alan Chhabra talks with theCUBE about the company’s collaboration with AWS, the role of databases in enabling AI applications and the MongoDB AI Applications Program.

“Our founders built their own modern database, because they wanted to make it easier to use data, whether it was for metadata use cases, operational and, today, vector data use cases,” said Alan Chhabra (pictured), executive vice president, partners, at MongoDB Inc. “We have hundreds of thousands of applications using MongoDB around the world [and] 50,000 paying customers. The hyperscalers … have done a great job creating an accelerator for customers [and] developers to get access to products like MongoDB and for MongoDB to be able to give them tools with [a] great experience.”

Chhabra spoke with theCUBE Research’s John Furrier for theCUBE’s “Cloud AWS re:Invent coverage,” during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed MongoDB’s collaboration with Amazon Web Services Inc., the role of databases in enabling AI applications and the introduction of the MongoDB AI Applications Program.

A new era for AI database integration

Amazon’s recent focus on foundational services, such as compute, storage and databases, underscores the importance of AI inference as a pivotal building block, according to Chhabra. MongoDB’s innovative AI Applications Program simplifies AI database integration by offering blueprints for developers to connect databases, language models and infrastructure.

“The MongoDB AI Applications Program takes partners, some competitors … and brings them together to give customers a blueprint,” Chhabra explained. “You need a blueprint for how to connect MongoDB via LangChain to Bedrock running on AWS with a data warehouse layer of Redshift.”

By collaborating with industry giants such as AWS, Google LLC and Microsoft Corp., along with consulting leaders such as McKinsey and Co. and Capgemini SE, the program accelerates the transformation of AI experiments into production-ready applications. These collaborations aim to deliver faster return on investment while tackling challenges such as data integration and operational scalability, according to Chhabra.

“The more of these blueprints, these recipes we can give to customers, the faster they get applications to production,” he said. “Today, we expanded our program to include Capgemini, McKinsey, IBM and Confluence, adding their own flavors to these recipes.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s “Cloud AWS re:Invent coverage”:

Photo: SiliconANGLE