Building Gen AI with MongoDB & AI Partners | September 2024

Last week I was in London for MongoDB.local London-the 19th stop of the 2024 MongoDB.local tour-where MongoDB, our customers, and our AI partners came together to share solutions we've been building that enable companies to accelerate their AI journey. I love attending these events because they offer an opportunity to celebrate our collective achievements, and because it's great to meet so many (mainly Zoom) friends in person!

One of the highlights of MongoDB.local London 2024 was the release of our reference architecture with our MAAP partners AWS and Anthropic, which supports memory-enhanced AI agents. This architecture is already helping businesses streamline complex processes and develop smarter, more responsive applications.

We also announced a robust set of vector quantization capabilities in MongoDB Atlas Vector Search that will help developers build powerful semantic search and generative AI applications with more scale-and at a lower cost. Now, with support for the ingestion of scalar quantized vectors, you can import and work with quantized vectors from your embedding model providers of choice, including MAAP partners Cohere, Nomic, and others.

A big thank you to all of MongoDB's AI partners, who continually amaze me with their innovation. MongoDB.local London was another great reminder of the power of collaboration, and I'm excited for what lies ahead as we continue to shape the future of AI together. As the Brits say: Cheers!

Welcoming new AI and tech partners

In September we also welcomed seven new AI and tech partners that offer product integrations with MongoDB. Read on to learn more about each great new partner!

Arize

Arize AI is a platform that helps organizations visualize and debug the flow of data through AI applications by quickly identifying bottlenecks in LLM calls and understanding agentic paths.

"At Arize AI, we are committed to helping AI teams build, evaluate, and troubleshoot cutting-edge agentic systems. Partnering with MongoDB allows us to provide a comprehensive solution for managing the memory and retrieval that these systems rely on", said Jason Lopatecki, co-founder and CEO of Arize AI. "With MongoDB's robust vector search and flexible document storage, combined with Arize's advanced observability and evaluation tools, we're empowering developers to confidently build and deploy AI applications."

Baseten

Baseten provides the applied AI research infrastructure needed to serve custom and open-source machine learning models performantly, scalably, and cost-efficiently.

"We're excited to partner with MongoDB to combine their scalable vector database with Baseten's high-performance inference infrastructure and high-performance models. Together, we're enabling companies to build and deploy generative AI applications, such as RAG apps, that not only scale infinitely but also deliver optimal performance per dollar," said Tuhin Srivastava, CEO of Baseten. "This partnership empowers developers to bring mission-critical AI solutions to market faster, while maintaining cost-effectiveness at every stage of growth."

Doppler

Doppler is a cloud-based platform that helps teams manage, organize, and secure secrets across environments and applications that can be used throughout the entire development lifecycle.

"Doppler rigorously focuses on making the easy path, the most secure path for developers. This is only possible with deep product partnerships with all the tooling developers have come to love. We are excited to join forces with MongoDB to make zero-downtime secrets rotation for non-relational databases effortlessly simple to set up and maintenance-free," said Brian Vallelunga, founder and CEO of Doppler. "This will immediately bolster the security posture of a company's most sensitive data without any additional overhead or distractions."

Haize Labs

Haize Labs automates language model stress testing at massive scales to discover and eliminate failure modes. This, alongside their inference-time mitigations and observability tools, enables the risk-free adoption of AI.

"We're thrilled to partner with MongoDB in empowering companies to build RAG applications that are both powerful yet secure, safe, and reliable," said Leonard Tang, co-founder and CEO of Haize Labs. "MongoDB Atlas has streamlined the process of developing production-ready GenAI systems, and we're excited to work together to accelerate customers' journey to trust and confidence in their GenAI initiatives."

Modal

Modal is a serverless platform for data and AI/ML engineers to run and deploy code in the cloud without having to think about infrastructure. Run generative AI models, large-scale batch jobs, job queues, and more, all faster than ever before.

"The coming wave of intelligent applications will be built on the potent combination of foundation models, large-scale data, and fast search," explained Charles Frye, AI Engineer at Modal. "MongoDB Atlas provides an excellent platform for storing, querying, and searching data, from hot new techniques like vector indices to old standbys like lexical search. It's the perfect counterpart to Modal's flexible compute, like serverless GPUs. Together, MongoDB and Modal make it easy to get started with this new paradigm, and then they make it easy to scale it out to millions of users querying billions of records & maxing out thousands of GPUs."

Portkey AI

Portkey AI is an AI gateway and observability suite that helps companies develop, deploy, and manage LLM-based applications.

"Our partnership with MongoDB is a game-changer for organizations looking to operationalize AI at scale. By combining Portkey's LLMOps expertise with MongoDB's comprehensive data solution, we're enabling businesses to deploy, manage, and scale AI applications with unprecedented efficiency and control," said Ayush Garg, Chief Technology Officer of Portkey AI. "Together, we're not just streamlining the path from POC to production; we're setting a new standard for how businesses can leverage AI to drive innovation and deliver tangible value."

Reka

Reka offers fully multimodal models including images, videos with audio, text, and documents to empower AI agents that can see, hear, and speak.

"At Reka, we know how challenging it can be to retrieve information buried in unstructured multimodal data. We are excited to join forces with MongoDB to help companies test and optimize multimodal RAG features for faster production deployment," said Dani Yogatama, CEO of Reka. "Our models understand and reason over multimodal data including text, tables, and images in PDF documents or conversations in videos. Our joint solution streamlines the whole RAG development lifecycle, speeding up time to market and helping companies deliver real values to their customers faster."

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.

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