Capgemini, Confluent, IBM, QuantumBlack, AI by McKinsey, and Unstructured join the MongoDB AI Applications Program (MAAP) ecosystem to help organizations make an impact with AI
MongoDB, Meta collaborating to support developers with Meta models and the end-to-end MAAP technology stack
Leading autism and intellectual and developmental disability software provider CentralReach using MAAP to improve AI-powered care platform
MAAP expansion follows the introduction of vector quantization to MongoDB Atlas Vector Search and recent AI partner integrations
LAS VEGAS, Dec. 2, 2024 /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB) today at AWS re:Invent announced that a new cohort of organizations have joined the MongoDB AI Applications Program (MAAP) ecosystem of leading 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, boosting the value customers receive from MAAP. Since it was launched earlier this year, MAAP has already made an impact, helping customers like CentralReach—which provides an AI-powered autism care and intellectual and developmental disabilities (IDD) platform—innovate with AI. The MAAP Center of Excellence Team, a cross-functional group of AI experts at MongoDB, has collaborated with partners and customers across industries to overcome an array of technical challenges, empowering organizations of all sizes to build and deploy AI applications. The expansion of the MongoDB AI Applications Program follows the introduction of vector quantization to MongoDB Atlas Vector Search (which reduces vector sizes while preserving performance—at lower cost), as well as new integrations with leading AI and technology companies.
MongoDB is also collaborating with Meta on Llama to support developers in their efforts to build more efficiently and to best serve customers. Currently, both enterprise and public sector 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 organizations 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. By joining the MAAP partner network, Capgemini, Confluent, IBM, QuantumBlack, AI by McKinsey, and Unstructured are helping the program evolve to meet the ever-changing AI landscape, and offering customers an array of leading solutions."
Launched in the summer of 2024—with founding members Accenture, Anthropic, Anyscale, Arcee AI, AWS, Cohere, Credal, Fireworks AI, Google Cloud, gravity9, LangChain, LlamaIndex, Microsoft Azure, Nomic, PeerIslands, Pureinsights, and Together AI—the MongoDB AI Applications Program is designed to help organizations unleash the power of their data and to take advantage of rapidly advancing AI technologies. It offers customers an array of resources to put AI applications into production: reference architectures and an end-to-end technology stack that includes integrations with leading technology providers, professional services, and a unified support system to help customers quickly build and deploy AI applications.
Because the AI landscape and customer expectations of AI continue to evolve, MongoDB has carefully grown the MAAP program—and the MAAP ecosystem of companies—to best meet customer needs. By working with AI industry leaders, MongoDB has gained a unique understanding of both the technology and implementation partners that can best help customers build AI applications, and has built the MAAP partner network accordingly.
New MAAP partners look forward to helping customers build AI applications
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 organizations."
"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 is the leading provider of ETL for LLMs, making it easy for enterprises to utilize 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."
Collaborating to make an impact with AI
Providing customers direct support from technical subject matter experts has been integral to MAAP's success. Since the program's inception, the MAAP Center of Excellence team—highly skilled AI experts from MAAP partners and groups across MongoDB—has worked with more than 150 organizations 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 automations for companies across industries.
A recent example of how MAAP enables organizations 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, and 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, Chief Technology Officer 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 program 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 everyday," 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."
Another success story is CentralReach, which provides an AI-powered electronic medical record (EMR) platform that is designed to improve outcomes for children and adults diagnosed with autism and related intellectual and developmental disabilities (IDD).
Prior to working with MongoDB and MAAP, CentralReach was looking for an experienced partner to further connect and aggregate its more than 4 billion financial and clinical data points across its suite of solutions.
CentralReach leveraged MongoDB's document model to aggregate the company's diverse forms of information from assessments to clinical data collection, so the company could build rich AI-assisted solutions on top of its database. Meanwhile, MAAP partners helped CentralReach to design and optimize multiple layers of its comprehensive buildout. All of this will enable CentralReach to support initiatives such as value-based outcome measurement, clinical supervision, and care delivery efficacy. With these new data layers in place, providers will be able to make substantial improvements to their clinical delivery to optimize care for all those they serve.
"As a mission-driven organization, CentralReach is always looking to innovate on behalf of the clinical professionals—and the more than 350,000 autism and IDD learners—that we serve globally," said Chris Sullens, CEO of CentralReach. "So being able to lean on MongoDBs database technology and draw on the collective expertise of the MAAP partner network—in addition to MongoDB's tech expertise and services—to help us improve outcomes for our customers and their clients worldwide has been invaluable."
The expansion of the MongoDB AI Applications Program builds on recent AI-related announcements from MongoDB.
In October, MongoDB announced vector quantization 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.
Outside of MAAP, since the start of the year MongoDB has built partnerships with more than 40 leading AI companies, enabling additional flexibility and choice for customers. Recent collaborations include those with Astronomer, Arize AI, Baseten, CloudZero, Modal, and ObjectBox. By working closely with its AI partners on product launches, integrations, and real-world challenges, MongoDB is able to bring a better understanding of AI to joint customers, deliver interoperability for end-to-end workflows, and to give them the resources and confidence they need to move forward with this groundbreaking technology.
To learn more about building AI-powered apps with MongoDB, please see our library of articles, tutorials, analyst reports, and white papers. And for more on the MongoDB AI Applications program, see the MAAP webpage.
About MongoDB
Headquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. Built by developers, for developers, MongoDB's developer data platform is a database with an integrated set of related services that allow development teams to address the growing requirements for a wide variety of applications, all in a unified and consistent user experience. MongoDB has more than 50,000 customers in over 100 countries. The MongoDB database platform has been downloaded hundreds of millions of times since 2007, and there have been millions of builders trained through MongoDB University courses. To learn more, visit mongodb.com.
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