MongoDB has introduced the MongoDB AI Applications Program (MAAP) to facilitate the rapid development and deployment of AI-powered applications for companies. MAAP gives organizations the necessary tools, including strategic advisory and professional services along with a comprehensive technology stack, to initiate their AI journey. The program strategically integrates consultancies, providers of foundation models, cloud infrastructure, generative AI frameworks, and model hosting with MongoDB Atlas. These collaborations aim to create tailored business solutions.

Alan Chhabra, MongoDB’s Executive Vice President of Worldwide Partners, remarked on the strong interest in generative AI across their customer base, which spans agile startups and well-established global enterprises. Chhabra observes that while enthusiasm for generative AI is widespread, about 25% of business leaders express a lack of readiness to deploy this technology effectively. Greg Maxson, MongoDB’s Senior Director of AI Go-To-Market and Strategic Partnerships, adds that companies often encounter obstacles due to a constantly shifting technology environment, a deficiency of in-house AI development skills, and the perceived risks of merging multiple vendor solutions.

MAAP’s Components:


Atlas serves is a comprehensive suite of databases and data services that support operations across multiple cloud environments. MongoDB has designed Atlas to offer pre-configured and optimized products, features, and services, thereby simplifying database management for developers and reducing the time to deployment.

Curated Partners:

MAAP includes a selection of consultancy partners tasked with evaluating a company’s current technology stack and pinpointing business challenges. These partners then craft strategic roadmaps for the companies to review, detailing the proposed architecture and the applications needed to address these challenges.

Top-of-Market Foundation Models: 

Leading foundation models from industry giants such as Anthropic, Cohere, Meta, Mistral, and OpenAI provide a diverse range of capabilities that cater to various business needs, letting companies choose the most appropriate model for their specific applications.

AI security: 

Security is a top concern in AI applications, and MAAP addresses this by incorporating services from Anyscale,, Together AI,, LangChain, and LlamaIndex. These services improve the security of AI applications, protecting data integrity and user privacy throughout the application lifecycle.

Cloud providers: 

MAAP benefits from MongoDB’s strategic partnerships with leading cloud providers like Amazon Web Services, Microsoft Azure, and Google Cloud. These relationships mean companies have the flexibility to deploy their AI solutions in the cloud environment that best fits their operational needs and preferences.

Prototyping assistance: 

Companies using MAAP can also take advantage of professional support to prototype their applications in a secure, private sandbox environment. These sessions, led by experts, focus on identifying and addressing internal business challenges using AI, helping to check the developed solutions are both practical and effective.

Generative AI-specialized consultancies: 

The program collaborates with consultancies that specialize in generative AI, such as PeerIslands, Pureinsights, and gravity9. These partners bring deep expertise in the field, helping them guide companies through the complexities of AI application development and make sure that the solutions are optimized for real-world use.

Strategic advantages

Three-layer AI stack

Scott Sanchez, MongoDB’s Vice President of Product Marketing and Strategy, elaborates on the structure of the AI technology stack, highlighting its three distinct layers. At the foundation of this stack lies the infrastructure, which includes GPUs and the AI models themselves. These elements are currently attracting much investment and attention due to their foundational importance in processing and executing complex AI tasks.

Above this infrastructure layer, at the top of the stack, reside the AI-powered applications. These are the end products that customers are actively looking to build or improve. These applications leverage AI to perform a range of tasks, from automating routine processes to providing complex analytics and insights.

Sandwiched between these two layers is where MongoDB asserts its presence — the data layer. Data acts as the linchpin that connects the computational power and models at the bottom with the functional applications at the top. Sanchez points out that the quality and integration of this data layer dictate the effectiveness of the entire AI application. A well-integrated data layer, enriched with real-time business data, transforms an AI application from a generic tool into a dynamic solution tailored to specific business needs.

MongoDB’s role is to facilitate this transformation by providing a comprehensive, flexible database that can handle the diverse and often intense demands of modern AI applications, ensuring data is not just stored but is actionable and directly feeds into AI processes.

Data as a differentiator

The approach to data integration and utilization separates MongoDB’s strategy from others. Instead of building generic AI applications that provide broad but shallow value, MongoDB focuses on making real-time data from the business environment a core part of the AI solution.

Scott Sanchez emphasizes that the choice between a generic AI solution and one that is deeply integrated with a company’s data can lead to vastly different outcomes. For businesses, leveraging real-time data effectively means their AI applications can respond more accurately to current events, predict outcomes more precisely, and provide more relevant insights, all of which are essential for maintaining competitive advantage.

MongoDB enables businesses to connect their operational data in ways that make these outcomes possible, arguing that the real-time, relevant connection of data sources through MongoDB can transform AI applications into highly adaptive, responsive tools that advance core business goals.

Enterprise benefits

Third-Party resources

With MAAP, MongoDB offers access to a wide range of third-party resources. These resources are designed to give businesses confidence in their AI development journey, from the security of the applications to their functional effectiveness. The partnerships and integrations available through MAAP mean that businesses do not have to guess if their AI applications will be useful or if they will deliver tangible business results.

These third-party resources include leading AI model providers, security tools, and cloud platforms, each vetted to complement MongoDB’s offerings and meet high standards of performance and reliability. Businesses using MAAP can expect not only technological compatibility but also strategic alignment with their broader goals, reducing the risk associated with AI projects.

Shortened development timelines

Greg Maxson reports that with MAAP, some customers have managed to reduce their AI application development and deployment timelines to approximately six weeks. This is a marked improvement over prior experiences, where development could take significantly longer due to challenges like integrating disparate technologies and navigating complex data landscapes.

The reduction in development time is attributed to several factors within MAAP, including the use of pre-configured environments, strategic guidance from expert partners, and the streamlined integration of external AI models and security services. These factors remove common barriers and accelerate the entire development process, allowing businesses to see the benefits of their AI investments sooner.

Availability and pricing

MongoDB announced that MAAP will be available to customers starting in July 2024. The impending launch gives businesses time to prepare and align their strategies with the capabilities that MAAP will offer. With the introduction of MAAP, MongoDB aims to democratize access to advanced AI tools, making it easier for more companies to embark on AI projects without the daunting overheads that typically come with such initiatives.

MongoDB has also indicated that the pricing model for MAAP will mirror its existing go-to-market model, which is designed to accommodate both independent and collaborative approaches. This model supports a variety of business sizes and types, from those who prefer to operate autonomously with minimal external assistance to those who seek comprehensive support through partnerships and collaborations.

This flexible pricing strategy means businesses can engage with MAAP in a manner that suits their budgetary and operational needs, making advanced AI accessible without necessitating a significant upfront investment. Companies can choose the level of investment that matches their current capabilities and growth ambitions, ensuring they can scale their AI initiatives in a sustainable manner.

Main takeaways

MongoDB is set to expand AI application development with its MongoDB AI Applications Program (MAAP), designed to simplify the integration of AI into business operations. MAAP simplifies the journey from strategic planning to deployment with tools, services, and a partner ecosystem that address common AI adoption challenges. Key features include the Atlas database suite, strategic consultancy partnerships, access to leading AI models, and prototyping support, all aimed at reducing development time and enhancing solution effectiveness.

Scott Sanchez emphasizes that MongoDB’s approach, focusing on data as the core link between AI’s computational base and its applications, enables businesses to turn generic AI tools into tailored solutions. As MAAP rolls out in July 2024, businesses can leverage MongoDB’s flexible pricing model to scale their AI initiatives efficiently, meaning solutions are advanced and aligned with strategic business objectives. This approach promises to make AI adoption more accessible, faster, and aligned with real-world business needs.

Alexander Procter

May 23, 2024

7 Min