MongoDB for Artificial Intelligence
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The landscape of AI workloads
Generative AI-enriched applications
Today's smart apps go beyond predictive analytics to create completely new experiences — from chatbots offering personalized support to AI-generated images, code, audio, and video — all from natural language inputs and in real time.
Traditional AI-enriched applications
Most modern applications leverage analytics to create more meaningful and reactive customer experiences. Through the use of machine learning models, AI automates complex decisioning for personalization, fraud prevention, predictive maintenance, and more.
Feature store and inference store
Feature stores are systems used to store and serve attributes used in machine learning models. Offline feature stores prioritize high throughput and are used for model training. Inference stores, or online feature stores, prioritize low latency for real-time inferences and serving live applications.
Resources for building AI-powered applications
Discover how to leverage MongoDB to streamline development for the next generation of AI-powered applications.
Core platform capabilities
“All of the business logic of our platform needs to make decisions very fast. It’s all running on Atlas, which allows us to move faster because we don’t have to worry about deploying or scaling. Whenever we need to add more fields, more queries, more steps in the business logic, Atlas just works. We don’t have to think about it.”
“With Atlas Vector Search now we have a comprehensive vector/metadata database – that’s been battle-tested over a decade – that solves our dense retrieval needs [to perform retrieval-augmented generation]. No need to deploy a new database we have to manage and learn.”
Build ML/AI applications with a suite of integrated data services
Application-Driven Intelligence: A guide for technology leaders
To compete and win in the digital economy you need to make your applications smarter. Smarter apps use data, AI, and analytics to engage users with natural language, generate insights and autonomously take action.
To build this new generation of apps, we need to do things differently. We can no longer rely on just copying our data out of operational systems into centralized analytics systems. Instead, we have to bring a new class of AI and analytics processing directly to the source of the data – to the applications themselves. We call this application-driven intelligence.
Defining the next wave of modern apps
MongoDB Atlas puts powerful AI and analytics capabilities directly into the hands of developers in ways that fit their workflows, frameworks, and languages.
Learn more about the requirements to successfully deliver application-driven intelligence and how you can get started.
MongoDB AI Innovators Program
Resources
Go from 0 to 1 to enterprise-ready with MongoDB Atlas and LLMs
Get started with MongoDB Atlas, popular generative AI frameworks, and LLMs to build your next-generation application that can perform at scale
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