MongoDB AI Applications Program welcomes more members

More organisations have joined the MongoDB AI Applications Program (MAAP) ecosystem of AI and tech companies. By lending their experience and expertise to MAAP, Capgemini, Confluent, IBM, QuantumBlack, AI by McKinsey, and Unstructured will offer customers additional integration and solution options.

MongoDB is also collaborating with Meta on Llama. Customers are leveraging Llama and MongoDB to build innovative, AI-enriched applications, accelerating progress toward business goals. In the coming months, MongoDB plans to implement turnkey mapping from its database to the LlamaStack APIs, empowering developers to deliver solutions to market more quickly and efficiently.

“At the beginning of 2024, many organisations saw the immense potential of generative AI, but were struggling to take advantage of this new, rapidly evolving technology. And 2025 is sure to bring more change—and further innovation,” said Greg Maxson, Senior Director of AI GTM and Strategic Partnerships at MongoDB.

“The aim of MAAP, and of MongoDB's collaborations with industry leaders like Meta, is to empower customers to use their data to build custom AI applications in a scalable, cost-effective way.”

Launched in 2024, MAAP offers customers resources to put AI applications into production, including reference architectures and an end-to-end technology stack that includes integrations with technology providers; professional services, and a support system.

A global consulting and technology services company, Capgemini offers integrated solutions for digital transformation, blending expertise with breakthrough technology. Confluent, meanwhile, is a cloud-native data streaming platform that allows users to stream, connect, process, and govern data in real time.

“Business leaders are increasingly recognizing generative AI’s value as an accelerator for driving innovation and revenue growth. But the real opportunity lies in moving from ambition to action at scale. We are pleased to continue working with MongoDB to help deliver tangible value to clients and drive competitive advantage by leveraging a trustworthy data foundation, thereby enabling gen AI at scale,” said Niraj Parihar, CEO of Insights & Data Global Business Line and Member of the Group Executive Committee at Capgemini.

“MAAP helps clients build gen AI strategy, identify key use cases, and bring solutions to life, and we look forward to being a key part of this for many organisations.”

“Enterprise AI strategy is inextricably dependent upon fresh, trusted data about the business. Without real-time datasets, even the most advanced AI solutions will fail to deliver value,” said Shaun Clowes, Chief Product Officer at Confluent.

“Seamlessly integrated with MongoDB and Atlas Vector Search, Confluent’s fully-managed data streaming platform enables businesses to build the trusted, always-up-to-date data foundation essential for powering gen AI applications.”

Unstructured provides extract, transform and load data mamanagement (ETL) for large language models (LLMs), making it easy for enterprises to utilise their unstructured data with gen AI systems.

“Like MongoDB, we understand that data is essential to harnessing the power of gen AI,” said Brian Raymond, Founder and CEO of Unstructured.

“We are excited to join the MongoDB AI Applications Program to bring our expertise in ingesting and preprocessing complex unstructured data for vector databases. The gen AI-ready data we continuously deliver and write to vector databases like MongoDB is essential to enabling our users to counter hallucinations, allowing the LLMs and AI projects that MAAP customers are working on to leverage sensitive, internal data while keeping models and projects up-to-date.”

Providing customers direct support from technical subject matter experts has been integral to the MAAP’s success, MongoDB said. The MAAP Center of Excellence team—highly skilled AI experts from MAAP partners and groups across MongoDB—has worked with more than 150 organisations on a range of technical challenges, including model and technology stack evaluation, chunking strategies, advanced retrieval techniques, and the establishment of agentic workflows. Example projects include working on sound diagnostic-based maintenance recommendations for a large manufacturer, and customer service automation.

A recent example of how MAAP enables organisations to build with AI is IndiaDataHub, which is on a mission to build India's largest market data and analytics platform. Since the company’s founding, MongoDB Atlas has been the platform’s operational database for some of its key datasets. Earlier this year, IndiaDataHub joined MAAP to access AI expertise, in-depth support, and a full spectrum of technologies to enhance AI functionality within its analytics platform. This includes connecting relevant data in MongoDB with Meta's AI models to perform sentiment analysis on text datasets.

”Data is the oil that will fuel the growth of the modern Indian economy,” said Pranoti Deshmukh, CTO at IndiaDataHub.

“Working with MongoDB, the MAAP ecosystem, and Meta's AI tools, we've been able to accelerate our AI strategy to make high-quality, timely data and analytics available to everyone in India who needs it. The professional support and deep AI expertise we've received through the MAAP programme have been outstanding."

“We are thrilled to see how many enterprises are leveraging our open source AI models to build better solutions for their customers and solve the problems their teams are facing every day,” said Ragavan Srinivasan, VP of Product at Meta.

“Leveraging our family of Meta models and the end-to-end technology stack offered by the MongoDB AI Applications Program demonstrates the incredible power of open source to drive innovation and collaboration across the industry.”

In October, MongoDB announced vector quantisation capabilities in MongoDB Atlas Vector Search. By reducing vector storage and memory requirements while preserving performance, these capabilities empower developers to build AI-enriched applications with more scale—and at a lower cost, the company said.

Outside of MAAP, MongoDB has built partnerships with more than 40 AI companies in 2024. Recent collaborations include those with Astronomer, Arize AI, Baseten, CloudZero, Modal, and ObjectBox.