Building Gen AI with MongoDB & AI Partners: May 2024

Gregory Maxson
June 5, 2024 | Updated: June 13, 2024
#Partners #genAI

Since I joined MongoDB last September, each month has seemed more action-packed than the last. But it’s possible that May was the busiest of all: May 2024 was a month of big milestones for MongoDB!

First, we held MongoDB.local NYC on May 2, our biggest .local event so far, with 2,500 attendees from around the world. It was the first MongoDB.local event I attended since joining the company, and suffice it to say I was thrilled to meet with so many colleagues and partners in person.

I was particularly excited to discuss the impact of MongoDB Atlas on the generative AI space, since we also announced the new MongoDB AI Applications Program (MAAP) in May.

Photo of MongoDB’s CEO, Dev Ittycheria, on the MongoDB .Local NYC keynote stage — MongoDB’s CEO, Dev Ittycheria, on the MongoDB .Local NYC keynote stage

MAAP was launched to help organizations quickly build, integrate, and deploy gen AI-enriched applications at scale. We do this by providing customers a complete package that includes strategic advisory, professional services, and a robust tech stack through MongoDB and our amazing partners: Anthropic, Anyscale, Amazon Web Services (AWS), Cohere, Credal.ai, Fireworks.ai, Google Cloud, gravity9, LangChain, LlamaIndex, Microsoft Azure, Nomic, PeerIslands, Pureinsights, and Together AI.

I really look forward to seeing how MAAP will empower customers to create secure, reliable, and high-performing gen AI applications after the program becomes publicly available in July. Stay tuned for more!

And if you’re interested in hearing more about MongoDB’s approach to AI partnerships, and how MAAP will help organizations of all sizes build gen AI applications, check out my interview with theCUBE at MongoDB.local NYC alongside Benny Chen, co-founder of Fireworks.ai.

Upcoming AI partner events

Are you in San Francisco in late June? We’re proud to sponsor the AI Engineer World’s Fair this year! Stop by the MongoDB booth to chat about gen AI development, and make sure to attend our panel “Building Your AI Stack with MongoDB, Cohere, LlamaIndex, and Together AI” on June 27.

Welcoming new AI partners

In addition to .local NYC and announcing MAAP in May, we also welcomed four AI partners that offer product integrations with MongoDB: Haystack, Mixpeek, Quotient AI, and Radiant. Read on to learn more about each great new partner.

Haystack is an open source Python framework for building custom apps with large language models (LLMs). It allows users to try out the latest models in natural language processing (NLP) while being flexible and easy to use.

“We’re excited to partner with MongoDB to help developers build top-tier LLM applications,” said Malte Pietsch, co-founder and CTO of deepset, makers of Haystack and deepset Cloud. “The new Haystack and MongoDB Atlas integration lets developers seamlessly use MongoDB data in Haystack, a reliable framework for creating quality LLM pipelines for use cases like RAG, QA, and agentic pipelines. Whether you're an experienced developer or just starting, your gen AI projects can quickly progress from prototype to adoption, accelerating value for your business and end-users."

Learn more about Haystack’s MongoDBAtlasDocumentStore to improve your AI applications.

Mixpeek is a multimodal indexing pipeline that gets a database ready for generative AI. It allows developers to treat an object store and a transactional database as a single entity.

Ethan Steininger, founder of Mixpeek, explained the value of the MongoDB-Mixpeek integration. “With MongoDB, developers store vectors, metadata, text and all the indexes needed for hyper-targeted retrieval,” he said. “Combined with Mixpeek, they can ensure their S3 buckets and all the documents, images, video, audio and text objects are always consistent with their transactional database, accelerating the path to production by instilling confidence that multimodal RAG results will always be up-to-date."

Read more about our partnership and learn how to build real-time multimodal vectors in a MongoDB cluster.

Quotient AI is a solution that offers developers the capability to evaluate their AI products with specialized datasets and frameworks to accelerate the experimentation cycle.

Julia Neagu, CEO of Quotient AI, highlighted the importance of our partnership. "We are excited to join forces with MongoDB and revolutionize how developers and enterprises are building AI products,” she said. “We share the common goal of helping developers get their ideas to market faster with a first-class developer experience. MongoDB Atlas scalable and versatile vector database technology complements Quotient's mission to ship high-quality, reliable AI applications through rapid, domain-specific evaluation."

Learn more how Quotient AI enables evaluation and refinement of RAG-powered AI products built on MongoDB Atlas.

Radiant offers a monitoring and evaluation framework for production AI use cases.

Nitish Kulnani, CEO of Radiant, shared his excitement about the partnership with MongoDB to enhance the reliability of AI applications. “By combining Radiant's anomaly detection with MongoDB Atlas Vector Search, we enable developers to swiftly identify and mitigate risks, and quickly deploy high-quality AI solutions, delivering real value to customers faster,” he said. “MongoDB trusts Radiant to accelerate its own AI applications, and we're excited to deliver the same experience to MongoDB customers.''

Read more about how to deploy Radiant with MongoDB Atlas to accelerate your journey from development to production.

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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Spinning Up Innovation: How MongoDB is Driving New Solutions at QSSTUDIO

Building bespoke innovations that address the needs of the future is the driving force behind the unique tech consultancy QSSTUDIO. With global venture capital funding forecast by EY to reach $12 billion this year for generative AI startups alone, the ability to bring ideas to life requires the right combination of technology and understanding of the app creation process. Led by Robin Tang, QSSTUDIO is a bespoke app and web platform development consultancy that provides professional digital expertise to dozens of small businesses, digital agencies, and startups in Australia and abroad. The flexibility of MongoDB Atlas, an integrated suite of data services, gives QSSTUDIO an instant launch pad for new ideas, allowing the team to easily spin-up new solutions and prototypes for clients. From skincare AI, to mining safety tools, and the petrol price tracking app ServoTrack, the team’s technological expertise combines with an understanding of data to bring these new ideas to market. QSSTUDIO has been able to keep its development team small, in part by using MongoDB Atlas Cluster, a NoSQL Database-as-a-Service in the cloud, which enables the team to easily test proof-of-concept designs and then migrate successful apps to Atlas without the need to reprovision the product. “We build bespoke solutions, and the flexibility and scalability of MongoDB Atlas has made it so much easier for us to quickly innovate and iterate, from concept inception to deployment,” Tang says. Tracking the ups and downs of Australia’s petrol prices With petrol prices soaring past AU$2.50/L, the ServoTrack app, founded by Robin Tang, is one of the best ways Australians can look for lower prices as they fluctuate during the week. Almost all of Australia’s state governments now supply unstructured data sources of real-time petrol price information. Tang wanted to create an app that allowed regular people to set alerts and be notified in real time of rises and falls in price. MongoDB Atlas provides the perfect solution to broadcast the data from these reputable sources. “The flexible data structure of MongoDB allows us to use different data schemas for data from different states. With geospatial indexing as well as Atlas Search Indexing, it provides a speedy way to allow users to find their target service station,” Tang says. “Atlas and MongoDB App services provide a few additional benefits for ServoTrack,” he added. “As expected for any cloud provider, the ability to scale whilst retaining automated backups means I could develop without worrying too much about our infrastructure.” Tang can leverage built-in features such as authentication, which allows users to sign in and store app preferences no matter how many devices they owned, whether it is on Android or iOS, as well as provide updates to users. “We use MongoDB Atlas to enable triggers on price changes at set service stations or general locations depending on the data available. This has helped to alert thousands of users of pending price increases, allowing them to save hundreds of dollars per year,” Tang says. RockShield: an innovative solution for miner safety QSSTUDIO created RockSHIELD software that has gone into the smart geotechnical instrumentation solutions delivered by SCT Operations. Recently, the underground mining and civil tunneling industry has undergone a digital transformation, with geotechnical instrumentation evolving from analogue to digital, resulting in more accurate field data that is accessed more frequently. Mining is an inherently high-risk operation, so it was essential to use this improved monitoring data to detect rock movement early and maintain a safer working environment for miners. Using MongoDB, Tang and his team created RockSHIELD’s software, which uses sensors to maintain mine safety by detecting the slightest movement in rocks. “We took the data on displacement, rotation, and angles from the rock sensors and put it into the MongoDB database which can handle flexible data sets,” Tang said. “Using MongoDB, we have the flexibility to store and receive data from a variety of sensors in different formats. The moment the numbers hit a threshold, the dashboard receives a notification that there is an issue. “The clients adopting this solution are very security conscious, and MongoDB’s security features make it attractive for our clients,” Tang says. “Our use of x.509 certificates for authentication, TLS/SSL communication, and Role Based Access Control let us create a hierarchy of access suitable for SCT Operations as well as RockSHIELD’s clients.” It was important to the team to create a system that works and is sustainable in the long-term to improve and maintain as high safety standards as possible. If you want to level-up your organization's innovation, or you’re a startup looking to build proof of concept, it's easy to get started with MongoDB Atlas today.

June 4, 2024

Next →

Hanabi Technologies Uses MongoDB to Power AI Assistant, Hana

For all the hype surrounding generative AI, cynics tend to view the few real-world implementations as little more than “fancy chatbots.” But for Abhinav Aggarwal, CEO of Hanabi Technologies, the idea of a generative AI-powered bot that is more than just an assistant was intriguing. “I’d been using ChatGPT since it launched,” said Aggarwal. “That got me thinking: How could we make a chatbot that was like a team member?” And with that concept, Hana was born. The problem with bots “Most generative AI chatbots do not act like people; they wait for a command and give a response,” said Aggarwal. “We wanted to create a human-like chatbot that would proactively help people based on what they wanted—automating reminders, for example, or fetching time zones from your calendar to correctly schedule meetings.” Hanabi’s flagship product, Hana, is an AI assistant designed to enhance team collaboration within Google Chat, working in concert with Google Workspace and its suite of products. “Our target customers are smaller companies of between 10 and 50 people. At this size you’re not going to build your own agent from scratch,” he said. Hana integrates with Google APIs to deliver a human-like assistant that chimes in with helpful interventions, such as automatically setting reminders and making sure meetings are booked in the right time zone for each participant. “Hana is designed to bring AI to smaller companies and help them collaborate in a space where they are already working—Google Workspace,” Aggarwal explained. The MongoDB Atlas solution For Hana to act like a member of the team, Hanabi needed to process massive amounts of data to support advanced features like retrieval-augmented generation (RAG) for better information retrieval across Google Docs and many other sources. And with a rapidly growing user base of over 600 organizations and 17,000+ installs, Hanabi also required a secure, scalable, and high-performing data storage solution. MongoDB Atlas provided a flexible document model, built-in vector database, and scalable cloud-based infrastructure, freeing Hanabi engineers to build new features for Hana rather than focusing on rote tasks like data extract, transform, and load processes or manual scaling and provisioning. Now, MongoDB Atlas handles a variety of responsibilities: Scalability and security: MongoDB Atlas’s auto-scaling and automatic backup features have enabled Hanabi to seamlessly grow its user base without the need for manual database management. RAG: MongoDB Atlas plays a critical role in Hana’s RAG functionality. The platform enables Hanabi to split Google Docs into small sections, create embeddings, and store these sections in Atlas’s vector database. Development Processes: According to Aggarwal, MongoDB’s flexibility in managing changing schemas has been essential to the company’s fast-paced development cycle. Data Visualization: Using MongoDB Atlas Charts has enabled Hanabi to create comprehensive dashboards for real-time data visualization. This has helped the team track usage, set reminders, and optimize performance without needing to build a manual dashboard. Impact and results With MongoDB Atlas, Hanabi can successfully scale Hana to meet the demands of its rapidly expanding user base. The integration is also enabling Hana to offer powerful features like automatic interactions with customers, advanced information retrieval from Google Docs, and manually added memory snippets, making it an essential tool for teams around the world. Next steps Hanabi plans to continue integrating more tools into Hana while expanding its reach to personal Gmail users. The company is also rolling out a new automatic-interaction feature, further enhancing Hana’s ability to proactively assist users without direct commands. MongoDB Atlas remains a key component of Hanabi’s stack, alongside Google Kubernetes Engine, NestJS, and LangChain, enabling Hanabi to focus on innovating to improve the customer experience. Tech Stack MongoDB Atlas Google Kubernetes Engine NestJS LangChain Are you building AI apps? Join the MongoDB AI Innovators Program today! Successful participants gain access to free MongoDB Atlas credits, technical enablement, and invaluable connections within the broader AI ecosystem. If your company is interested in being featured, we’d love to hear from you. Connect with us at ai_adopters@mongodb.com.

November 21, 2024