Building Gen AI with MongoDB & AI Partners | January 2025

Gregory Maxson
February 11, 2025
#Partners #ArtificialIntelligence #genAI

Even for those of us who work in technology, it can be hard to keep track of the awards companies give and receive throughout the year. For example, in the past few months MongoDB has announced both our own awards (such as the William Zola Award for Community Excellence) and awards the company has received—like the AWS Technology Partner of the Year NAMER and two awards from RepVue. And that’s just us! It can be a lot!

But as hard as they can be to follow, industry awards—and the recognition, thanks, and collaboration they represent—are important. They highlight the power and importance of working together and show how companies like MongoDB and partners are committed to building best-in-class solutions for customers.

So without further ado, I’m pleased to announce that MongoDB has been named Technology Partner of the Year in Confluent’s 2025 Global Partner Awards! As a member of the MongoDB AI Applications Program (MAAP) ecosystem, Confluent enables businesses to build a trusted, real-time data foundation for generative AI applications through seamless integration with MongoDB and Atlas Vector Search.

Above all, this award is a testament to MongoDB and Confluent’s shared vision: to help enterprises unlock the full potential of real-time data and AI. Here’s to what’s next!

Welcoming new AI and tech partners

It's been an action-packed start to the year: in January 2025, we welcomed six new AI and tech partners that offer product integrations with MongoDB. Read on to learn more about each great new partner!

Base64

Base64 is an all-in-one solution to bring AI into document-based workflows, enabling complex document processing, workflow automation, AI agents, and data intelligence.

“MongoDB provides a fantastic platform for storing and querying all kinds of data, but getting unstructured information like documents into a structured format can be a real challenge. That's where Base64 comes in. We're the perfect onramp, using AI to quickly and accurately extract the key data from documents and feed it right into MongoDB,” said Chris Huff, CEO of Base64. “This partnership makes it easier than ever for businesses to unlock the value hidden in their documents and leverage the full power of MongoDB."

Dataloop

Dataloop is a platform that allows developers to build and orchestrate unstructured data pipelines and develop AI solutions faster.

"We’re thrilled to join forces with MongoDB to empower companies in building multimodal AI agents”, said Nir Buschi, CBO and co-founder of Dataloop. “Our collaboration enables AI developers to combine Dataloop’s data-centric AI orchestration with MongoDB’s scalable database. Enterprises can seamlessly manage and process unstructured data, enabling smarter and faster deployment of AI agents. This partnership accelerates time to market and helps companies get real value to customers faster."

Maxim AI

Maxim AI is an end-to-end AI simulation and evaluation platform, helping teams ship their AI agents reliably and more than 5x faster.

“We're excited to collaborate with MongoDB to empower developers in building reliable, scalable AI agents faster than ever,” said Vaibhavi Gangwar, CEO of Maxim AI. “By combining MongoDB’s robust vector database capabilities with Maxim’s comprehensive GenAI simulation, evaluation, and observability suite, this partnership enables teams to create high-performing retrieval-augmented generation (RAG) applications and deliver outstanding value to their customers.”

Mirror Security

Mirror Security offers a comprehensive AI security platform that provides advanced threat detection, security policy management, continuous monitoring ensuring compliance and protection for enterprises.

“We're excited to partner with MongoDB to redefine security standards for enterprise AI deployment,” said Dr. Aditya Narayana, Chief Research Officer, at Mirror Security. “By combining MongoDB's scalable infrastructure with Mirror Security's end-to-end vector encryption, we're making it simple for organizations to launch secure RAG pipelines and trusted AI agents. Our collaboration eliminates security-performance trade-offs, empowering enterprises in regulated industries to confidently accelerate their AI initiatives while maintaining the highest security standards.”

Squid AI

Squid AI is a full-featured platform for creating private AI agents in a faster, secure, and automated way.

“As an AI agent platform that securely connects to MongoDB in minutes, we're looking forward to helping MongoDB customers reveal insights, take action on their data, and build enterprise AI agents,” said Leslie Lee, Head of Product at Squid AI. “By pairing Squid's semantic RAG and AI functions with MongoDB's exceptional performance, developers can build powerful AI agents that respond to new inputs in real-time.”

TrojAI

TrojAI is an AI security platform that protects AI models and applications from new and evolving threats before they impact businesses.

“TrojAI is thrilled to join forces with MongoDB to help companies secure their RAG-based AI apps built on MongoDB,” said Lee Weiner, CEO of TrojAI. “We know how important MongoDB is to helping enterprises adopt and harness AI. Our collaboration enables enterprises to add a layer of security to their database initialization and RAG workflows to help protect against the evolving GenAI threat landscape.”

But what, there’s more!

In February, we’ve got two webinars coming up with MAAP partners that you don’t want to miss:

Build a JavaScript AI Agent With MongoDB and LangGraph.js: Join MongoDB Staff Developer Advocate Jesse Hall and LangChain Founding Software Engineer Jacob Lee for an exclusive webinar that highlights the integration of LangGraph.js, LangChain’s cutting-edge JavaScript library, and MongoDB - live on Feb 25.
Architecting the Future: RAG and Al Agents for Enterprise Transformation: Join MongoDB, LlamaIndex, and Together AI to explore how to strategically build a tech stack that supports the development of enterprise-grade RAG and AI agentic systems, explore technical foundations and practical applications, and learn how the MongoDB Applications Program (MAAP) will enable you to rapidly innovate with AI - content on demand.

To learn more about building AI-powered apps with MongoDB, check out our AI Learning Hub and stop by our Partner Ecosystem Catalog to read about our integrations with MongoDB’s ever-evolving AI partner ecosystem.

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Simplify Security At Scale with Resource Policies in MongoDB Atlas

Innovation is the gift that keeps on giving: industries that are more innovative have higher returns, and more innovative industries see higher rates of long-term growth 1 . No wonder organizations everywhere strive to innovate. But in the pursuit of innovation, organizations can struggle to balance the need for speed and agility with critical security and compliance requirements. Specifically, software developers need the freedom to rapidly provision resources and build applications. But manual approval processes, inconsistent configurations, and security errors can slow progress and create unnecessary risks. Friction that slows down employees and leads to insecure behavior is a significant driver of insider risk. Paul Furtado Vice President, Analyst, Gartner Enter resource policies , which are now available in public preview in MongoDB Atlas. This new feature balances rapid innovation with robust security and compliance. Resource policies allow organizations to enable developers with self-service access to Atlas resources while maintaining security through automated, organization-wide ‘guardrails’. What are resource policies? Resource policies help organizations enforce security and compliance standards across their entire Atlas environment. These policies act as guardrails by creating organization-wide rules that control how Atlas can be configured. Instead of targeting specific user groups, resource policies apply to all users in an organization, and focus on governing a particular resource. Consider this example: An organization subject to General Data Protection Regulation (GDPR) 2 requirements needs to ensure that all of their Atlas clusters run only on approved cloud providers in regions that comply with data residency and privacy regulations. Without resource policies, developers may inadvertently deploy clusters on any cloud provider. This risks non-compliance and potential fines of up to 20 million euros or 4% of global annual turnover according to article 83 of the GDPR. But, by using resource policies, the organization can mandate which cloud providers are permitted, ensuring that data resides only in approved environments. The policy is automatically applied to every project in the organization, preventing the creation of clusters on unauthorized cloud platforms. Thus compliance with GDPR is maintained. The following resource policies are now in public preview: Restrict cloud provider: Limit Atlas clusters to approved cloud providers (AWS, Azure, Google Cloud). Restrict cloud region: Restrict cluster deployments in approved cloud providers to specific regions. Block wildcard IP: Reduce security risk by disabling the use of 0.0.0.0/0 (or “wildcard”) IP address for cluster access. How resource policies enable secure self-service Atlas access Resource policies address the challenges organizations face when trying to balance developer agility with robust security and compliance. Without standardized controls, there is a risk that developers will configure Atlas clusters to deviate from corporate or external requirements. This invites security vulnerabilities and compliance gaps. Manual approval and provisioning processes for every new project creates delays. Concurrently, platform teams struggle to enforce consistent standards across an organization, increasing operational complexity and costs. With resource policies, security and compliance standards are automatically enforced across all Atlas projects. This eliminates manual approvals and reduces the risk of misconfigurations. Organizations can deliver self-service access to Atlas resources for their developers. This allows them to focus on building applications instead of navigating complex internal review and compliance processes. Meanwhile, platform teams can manage policies centrally. This ensures consistent configurations across the organization and frees time for strategic initiatives. The result is a robust security posture, accelerated innovation, and greater efficiency. Automated guardrails prevent unauthorized configurations. Concurrently, centralized policy management streamlines operations and ensures alignment with corporate and external standards. Resource policies enable organizations to scale securely and innovate without compromise. This empowers developers to move quickly while simplifying governance. Creating resource policies Atlas resource policies are defined using the open-source Cedar policy language , which combines expressiveness with simplicity. Cedar’s concise syntax makes writing and understanding policies easy, streamlining policy creation and management. Resource policies can be created and managed programmatically through infrastructure-as-code tools like Terraform or CloudFormation, or by integrating directly using the Atlas Admin API. To explore what constructing a resource policy looks like in practice, let’s return to our earlier example. This is an organization subject to GDPR requirements that wants to ensure all of their Atlas clusters run on approved cloud providers only. To prevent users from creating clusters on Google Cloud (GCP), the organization could write the following policy named “ Policy Preventing GCP Clusters .” This policy forbids creating or editing a cluster when the cloud provider is Google Cloud. The body defines the behavior of the policy in the human and machine-readable Cedar language. If required, ‘ gcp ’ could be replaced with ‘ aws ’. Figure 1. Example resource policy preventing the creation of Atlas clusters on GCP. Alternatively, the policy could allow users to create clusters only on Google Cloud with the following policy named “Policy Allowing Only GCP Clusters”. This policy uses the Cedar clause “unless” to restrict creating or editing a cluster unless it is on GCP. Figure 2. Example resource policy that restricts cluster creation to GCP only. Policies can also have compound elements. For example, an organization can create a project-specific policy that only enforces the creation of clusters in GCP for the Project with ID 6217f7fff7957854e2d09179 . Figure 3. Example resource policy that restricts cluster creation to GCP only for a specific project. And, as shown in Figure 4, another policy might restrict cluster deployments on GCP as well as on two unapproved AWS regions: US-EAST-1 and US-WEST-1. Figure 4. Example resource policy restricting cluster deployments on GCP as well as AWS regions US-EAST-1 and US-WEST-1. Getting started with resource policies Resource policies are available now in MongoDB Atlas in public preview. Get started creating and managing resource policies programmatically using infrastructure-as-code tools like Terraform or CloudFormation. Alternatively, integrate directly with the Atlas Admin API. Support for managing resource policies in the Atlas user interface is expected by mid-2025. Use the resources below to learn more about resource policies. Feature documentation Postman Collection Atlas Administration API documentation Terraform Provider documentation AWS CDK AWS Cloud Formation documentation 1 McKinsey & Company , August 2024 2 gdpr.eu

February 10, 2025

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MongoDB Empowers ISVs to Drive SaaS Innovation in India

Independent Software Vendors (ISVs) play a pivotal role in the Indian economy. Indeed, the Indian software market is expected to experience an annual growth rate of 10.40%, resulting in a market volume of $15.89bn by 2029. 1 By developing specialized software solutions and digital products that can be bought 'off the shelf', ISVs empower Indian organizations to innovate, improve efficiency, and remain competitive. Many established enterprises in India choose a 'buy' rather than 'build' strategy when it comes to creating modern software applications. This is particularly true when it comes to cutting-edge AI use cases. MongoDB works closely with Indian ISVs across industries, providing them with a multi-cloud data platform and highly flexible, scalable technologies to build operational and efficient software solutions. For example, Intellect AI , a business unit of Intellect Design Arena, has used MongoDB Atlas to drive a number of innovative use cases in the banking, financial services, and insurance industries. Intellect AI chose MongoDB for its flexibility coupled with its ability to meet complex enterprise requirements such as scale, resilience, and security compliance. And Ambee, a climate tech startup, is using MongoDB Atlas ’ flexible document model to support its AI and ML models. Here are three more examples of ISV customers who are enabling, powering, and growing their SaaS solutions with MongoDB Atlas. MongoDB enhancing Contentstack's content delivery capabilities Contentstack is a leading provider of composable digital experience solutions, and specializes in headless content management systems (CMS). Headless CMS is a backend-only web content management system that acts primarily as a content repository. “Our headless CMS allows our customers to bring all forms of content to the table, and we host the content for them,” said Suryanarayanan Ramamurthy, Head of Data Science at Contentstack, while speaking at MongoDB.local 2024 . A great challenge in the CMS industry is the ability to provide customers with content that remains factually correct, brand-aligned, and tailored to the customer’s identity. Contentstack created an innovative, AI-based product— Brand Kit —that does exactly that, built on MongoDB Atlas. “Our product Brand Kit, which launched in June 2024, overcomes factual incorrectness. The AI capabilities the platform offers help our customers create customized and context-specific content that meets their brand guidelines and needs,” said Ramamurthy. MongoDB Atlas Vector Search enables Contentstack to transform content and bring contextual relevance to retrievals. This helps reduce errors caused by large language model hallucinations, allowing the retrieval-augmented generation (RAG) application to deliver better results to users. AppViewX: unlocking scale for a growing cybersecurity SaaS pioneer AppViewX delivers a platform for organizations to manage a range of cybersecurity capabilities, such as certificate lifecycle management and public key infrastructure. The company ensures end-to-end security compliance and data integrity for large enterprises across industries like banking, healthcare, and automotive. Speaking at MongoDB.local Bengaluru in 2024, Karthik Kannan, Vice President of Product Management at AppViewX, explained how AppViewX transitioned from an on-premise product to a SaaS platform in 2021. MongoDB Atlas powered this transition. MongoDB Atlas's unique flexibility, scalability, and multi-cloud capabilities enabled AppViewX to easily manage fast-growing data sets, authentication, and encryption from its customers’ endpoints, device identities, workload identities, user identities, and more. Furthermore, MongoDB provides AppViewX with robust security guaranteeing critical data protection, and compliance. “We've been really able to grow fast and at scale across different regions, gaining market share,” said Kannan. “Our engineering team loves MongoDB,” added Kannan. “The support that we get from MongoDB allowed us to get into different regions, penetrate new markets to grow at scale, so this is a really important partnership that helped us get to where we are.” Zluri Streamlines SaaS Management with MongoDB Zluri provides a unified SaaS management platform that helps IT and security teams manage applications across the organization. The platform provides detailed insights into application usage, license optimization, security risks, and cost savings opportunities. Zluri processes massive volumes of unstructured data—around 9 petabytes per month—from over 800 native integrations with platforms like single sign-on, human resources management systems, and Google Workspace. One of its challenges was to automate the discovery and data analysis across those platforms, as opposed to employing an exhaustive time and labour intensive manual approach. MongoDB Atlas has allowed Zluri to ingest, normalize, process, and manage the high volume and complexity of data seamlessly across diverse sources. “We wanted to connect with every single system that's currently available, get all that data, process all that data so that the system works on autopilot mode, so that you're not manually adding all that information,” said Chaithaniya Yambari, Zluri’s Co-Founder and Chief Technology Officer, when speaking at MongoDB.local Bengaluru in 2024 . As a fully managed database, MongoDB Atlas platform allows Zluri to eliminate maintenance overhead, so its team of engineers and developers can focus on innovation. Zluri also utilizes MongoDB Atlas Search to perform real-time queries, filtering, and ranking of metadata. This eliminates the challenges of synchronizing separate search solutions with the database, ensuring IT managers get fast, accurate, and up-to-date results. These are just a few examples of how MongoDB’s is working with ISVs to shape the future of India’s digital economy. As technology continues to evolve, the role of ISVs in fostering innovation and economic growth will become ever more integral. MongoDB is committed to providing ISVs with a robust, flexible, and scalable database that removes barriers to growth and the ability to innovate. Visit our product page to learn more about MongoDB Atlas. Learn more about MongoDB Atlas Search on our product details page. Check out our Quick Start Guide to get started with MongoDB Atlas Vector Search today.

February 11, 2025