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Building Gen AI with MongoDB & AI Partners | August 2024

As the AI landscape continues to evolve, companies, industries, and developers seek tailored solutions to their unique challenges. Gone are the days when general-purpose AI models could be applied universally. Now, organizations are looking for industry-specific applications, verticalized AI solutions, and specialized tools to gain a competitive edge and best serve their customers. And as gen AI use cases have diversified—from healthcare diagnostics and autonomous driving, to personalized recommendations and creative content generation—so has the technology stack supporting them.The complexity of building and deploying AI models has led to the rise of specialized AI frameworks and platforms that streamline workflows and optimize performance for specific use cases. In this context, having the right AI stack is essential for driving innovation. AI development is no longer just about choosing the best model but also about selecting the right tools, libraries, and infrastructure to support that model across the board.All of which makes partnerships (and combining technical strengths) increasingly important to innovating with AI. Take, for example, our most recent integration with LangChain: the MongoDB-LangChain partnership exemplifies how having the right components in an AI stack allows teams to focus on innovating instead of managing infrastructure bottlenecks. By combining LangGraph with MongoDB’s vector search capabilities, developers can create more sophisticated, high-performing AI applications. This integration allows for the seamless development of agentic AI systems capable of generating actionable insights and delivering complex tasks.To learn more about building powerful AI agents with LangGraph.js and MongoDB, plus our recent work making vector search even more versatile with custom LangChain Retrievers, check out our tutorial.Welcoming new AI partnersMongoDB’s partnership with LangChain highlights the importance of building adaptable solutions that can grow and change as the needs of developers and customers grow and change.Which is why MongoDB is always on the lookout for innovative partners and solutions—in August we welcomed five new AI partners that offer product integrations with MongoDB. Read on to learn more about each great new partner!BuildShip BuildShip is a low-code visual backend and workflow builder to instantly create APIs, scheduled tasks, backend cloud jobs, and automation, powered by AI.”We at BuildShip are thrilled to partner with MongoDB to introduce an innovative low-code approach for rapidly building AI workflows and backend tasks in a visual and scalable manner,” said Harini Janakiraman, CEO of BuildShip.com. “MongoDB offers a comprehensive data stack for AI developers and organizations, enabling them to efficiently build scalable databases and access vector or hybrid search options for their products. Our collaboration provides customizable low-code templates that allow for easy integration of MongoDB databases with a variety of AI models and tools. This enables teams and companies to quickly build powerful APIs, automations, vector search, and scheduled tasks, unlocking organizational efficiency and driving product innovation.”Inductor Inductor is a platform to prototype, evaluate, improve, and observe LLM apps and features, helping developers ship high-quality LLM-powered functionality rapidly and systematically.“We’re excited to partner with MongoDB to enable companies to rapidly create production-grade LLM applications, by combining MongoDB’s powerful vector search with Inductor’s developer platform enabling streamlined, systematic workflows for developing RAG-based applications,” said Ariel Kleiner, CEO of Inductor. “While many LLM-powered demos have been created, few have successfully evolved into production-grade applications that deliver business wins. Together, Inductor and MongoDB enable enterprises to build impactful, needle-moving LLM applications, accelerating time to market and delivering real value to customers.”Metabase Metabase is the easy-to-use, open source Business Intelligence tool that lets everyone work with data, with or without SQL, for internal and customer-facing, embedded analytics.”This partnership is an important step forward for NoSQL database analytics. By integrating Metabase with MongoDB, two popular open-source tools, we are making it easier for users to quickly get valuable insights from their MongoDB data,” explained Luiz Arakaki, Product Manager at Metabase. “Our goal is to create a better integration between the tools to offer more advanced features and stability, simplifying the use of NoSQL databases for advanced analytics.”Shakudo Shakudo is a comprehensive development platform that lets data professionals develop, run, and deploy data pipelines and applications in an all-in-one integrated environment.“Shakudo is thrilled to be partnering with MongoDB to streamline the entire retrieval-augmented generation (RAG) development lifecycle. Together we help companies test and optimize their RAG features for faster PoC, and production deployment,” noted Yevgeniy Vahlis, CEO of Shakudo. “MongoDB has made it dead simple to launch a scalable vector database with operational data, and Shakudo brings industry leading AI tooling to that data. Our collaboration speeds up time to market and helps companies get real value to customers faster.”VLM Run VLM Run is a versatile API that enables accurate JSON extraction from any visual content such as images, videos, and documents, helping users to integrate visual AI to applications.“VLM Run is excited to partner with MongoDB to help enterprises accurately extract structured insights from visual content such as images, videos and visual documents,” said Sudeep Pillai, Co-Founder and CEO of VML Run. “Our combined solution will enable enterprises to turn their often-untapped unstructured visual content into actionable, queryable business intelligence.”But wait, there’s more!To learn more about building AI-powered apps with MongoDB, check out our AI Resources Hub, and stop by our Partner Ecosystem Catalog to read about our integrations with MongoDB’s ever-evolving AI partner ecosystem.

September 11, 2024