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Peder Ulander

CMO

MongoDB

Mona Chadha

Director of Category Management

AWS

MongoDB accelerates AI development with new Amazon Bedrock integration

Among several announcements made by MongoDB Inc. today was the news that Atlas Vector Search Integration with Knowledge Bases on Amazon Bedrock had mo...

play_circle_outline Introduction of Peder Ulander and Mona Chadha's roles at MongoDB and AWS

play_circle_outline Discussion of the integration of AWS Marketplace and AWS Partner Network

play_circle_outline Overview of the benefits of the MongoDB AI Application Program ($map)

play_circle_outline Emphasis on the role of AWS Marketplace in simplifying the procurement process

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Peder Ulander | MongoDB & Mona Chadha | AWS

Peder Ulander

CMO MongoDB

Mona Chadha

Director of Category Management AWS

>> Welcome back to MongoDB.local here in New York City. Come on inside theCUBE, we got a great conversation here. MongoDB. He made all this happen, and of course, with his team. And Mona Chadha is the director of category management at AWS. Great to see you guys. What's happening?

Peder Ulander

>> Thanks for having us here.

>> You guys both been on theCUBE before.

Mona Chadha

>> Yes.

>> Mona, what's happening in your world? Tell us about your role. Let's start there.

Mona Chadha

>> Yeah, I head up all of our, what we call infrastructure ISVs. And so my team manages all of the partnerships for ISVs that fall into categories like security, networking, storage, database, data and analytics, AIML, generative AI, DevOps, So think of this as a team that manages partnerships, everything except for a business application. And so MongoDB is one of our key strategic partners where we've been working together for... Gosh, I mean, I've been with for 11 years, 11 plus years. And I can't imagine a time where I wasn't working with MongoDB. So yeah, we've been a long-time partners and really helping to get ISVs to integrate to services and deliver those to our end customers or joint end

>> It wasn't that long ago, correct me if I'm wrong, that you guys merged the APN network and that gives you way more scale and flywheel to use your I mean, what we did was we merged our AWS Marketplace into the AWS partner network. So what that did was MongoDB has been a seller, if you will, on AWS Marketplace. And what that does is it provides all of the software and services that ISVs provide merged into the partner network. So now it's just a broader partnership that spans not only co-sell with us as partners, but also all of the business that transacts through the Marketplace.

>> I was on an analyst briefing last night for Q, and they were basically describing this sort of new strategy that Amazon Web Services has for communications, which is, We always get the Firehose at re:Invent,and they were talking about basically more Firehoses throughout the year. So I saw Swami the other day on LinkedIn. He released some stuff. The Q announcement that we got briefed on last night, you got... So part of, I think, Swami's was the gen AI competency launch, that was part of his Firehose. Explain what that is, and I'm dying to know what Mongo thinks about it.

Mona Chadha

>> Yeah, yeah. No, that's great. So first, let me explain sort of the concept of what we mean by AWS competencies, partner competencies. And what that essentially is what we found is that our partners have very differentiated skill sets. They offer a variety of different solutions, and they start to develop skill sets and the expertise around integration with services. So we want to do is make sure that our customers were exposed to all of our different partner solutions that integrated to services. And then in turn, those partners can help customers with integrations into their applications. And so the competencies span different tools, infrastructure applications across different partners like SIs, ISVs. And so, one of the other key areas that we created a competency around is around generative AI. So as we are building out our generative AI services like Amazon Bedrock, and Q, and SageMaker, we to ensure that customers had exposure to all the different partner integrations associated to that. And so as a result, we have a variety of different integrations across multiple competencies within... We launched the generative AI competency back in March-- March 6th, early in March. And MongoDB is one of the partners that is a part of our generative AI competency. And that, again, just gives our customers that added benefit of having access to partner solutions. the key thing about these competencies is that they're vetted, right? We have a high security bar, so the customers have trust in any partner that is part of the competency program.

>> Like So you're a trusted part. Okay, so what's your angle here?

Peder Ulander

>> Yeah, no, I mean it's exactly that. I think you heard Dave this morning in the keynote. He said, especially in gen AI, 87of executives, they know they need to get into gen AI. They don't know where to start. And when you look at the ecosystem technologies that are out there, every week, hundreds of new services or solutions are coming out. So how do I know is going to work for me? How do I know these pieces are going to work together? That's such a critical component. And so when you think about AWS with now... What do you have? 275,

Mona Chadha

>> Over 200 services, yes.

Peder Ulander

>> When you think about just their own ecosystem of stuff, how do you know when I choose MongoDB that it's going to work with Bedrock, it's going to work with Q, that the integrations are going to be there to remove the friction and enable me to move quickly? The competency becomes kind of that badge of trust, support, and knowledge that it is the right way to get started with these technologies working together. So if anything, you think back to the original days where it was nothing more than a certified partner and it was a stamp. This is taking that way further along because it comes with all of the tools, documentation, guarantees, APIs, and integrations that customers need.

>> That integration is key. It's real engineering work. And now you also announced that your GA and Bedrock, what does that mean? What's specifically?

Peder Ulander

>> Well, so... You'll speak better about Bedrock than I will, but I think at the end of the day, Bedrock is kind of that orchestrational area. You can almost call it like an AI path. It brings together components from infrastructure, orchestration, tooling, et cetera, et cetera, really focused on building gen AI apps and removing the friction and complexity in developers building this stuff up or operating it, right? Well, as part of building an application, you need a database. So MongoDB comes in, we sit with Bedrock, it enables us to have the developers use the tools for building the apps that they want to use, knowing full well that they don't have to leave that console to come to our console to integrate MongoDB. We're part of the overall orchestration unit so they can move quickly.

>> I like the way Peder explained that because I think a lot of times AWS has misunderstood. People think LLMs equal AI, and we know, we've applied it, and it's just not that simple, especially if we want to get real business value out of it. You need all these other frameworks and tools. People talk about guardrails or what does that mean? You need security, you need to make sure the LLM's not leaking data, et cetera. So what would you add to that Bedrock?yeah. No, I think in terms of that integration, one of the key things that we heard from customers too is... And you're right, AI is beyond just an LLM or a large language model. There's many layers of it. And that's why AWS has sort of constructed our approach to AI with having the infrastructure available, the compute, the chip sets with kind of Amazon Bedrock in the sort of middle layer where, again, we want to give customers choice in terms of what type of foundational models they can use and integrate into their applications and be able to readily use that in their real world applications. So I think this is just the tip of the iceberg in terms of the integration work that we're doing together with Bedrock, but we're just seeing a ton of customer feedback and the desire to say, We need help getting started with generative AI, and this gets us in the right

>> And we saw the big announcement. I guess, it was yesterday, was the Mongo AI application program, map. Amazon is obviously part of that, as are a number of others. Tell people why they should care about this, why it's important for them, and then I'm interested in why it's important for MongoDB.

Peder Ulander

>> So building on that, I mean, you're seeing a common thread here, right? Customers want to have the easy button to get started. They want to have the guarantees that things are working together. And the third frame of that is they want to know that it's going to be applicable to the use case of the business problem that they're trying to solve. And we saw a huge opportunity in the fact that over the last year, we've been working across various industries: retail, finance, telco, et cetera, helping them kind of get started on that AI journey. We saw specific use cases, development, architectural patterns, and technologies that were really, really critical in helping them get moving quickly. So map brings together that rich ecosystem with validated reference designs based on the use cases they're trying to achieve and the integrations into all of the technologies that are required to go do so. Obviously, in this AI journey, hyperscalers play an outsized role in getting customers moving and the work that Amazon's doing on Bedrock and Q and everything else just makes them such a critical piece of that partnership.

>> So there's synergies there.

Peder Ulander

>> Oh, yeah.And no, just to even further emphasize the point, customers really need prescriptive guidance in terms of how to get started with AI. Everyone just thinks AI is about a chatbot. It is not. It is not. And so it's way more complicated than that. And so having programs like map, and we were really excited to join map because, again, we're giving customers more guidance in terms of, Here's how you get started, here are the use cases.And one of the things that I think marries really well into map is also we've provided our customers with an AI use case Explorer to again help them through, Here are all the different ways,in all the different industries that customers are using AWS services plus third-party software services, data, et cetera. And that really has helped end customers navigate and get started with generative AI faster.

>> So there's ideas in there, and there's also package solutions-

Mona Chadha

>> Blueprint type of solutions, yeah.

Peder Ulander

>> and package solutions. And then also the component of map is also the services piece. So on one side it could be an exploratory service to say what use cases are going to be the starting point? What's going to get me moving with the biggest impact? That level of services is really, really critical. Or there's another one: you've decided on the use case you want. This is how we bring those blueprints, reference architectures and integrations forward so that you can move from ideation to market as fast as possible.

>> And you mentioned Marketplace before. That's been huge. I think it's really a differentiator for AWS and its partners. How have you leveraged Marketplace? What does that mean for your relationship?

Peder Ulander

>> Oh, yeah. No, Marketplace is such a critical part of the relationship we have with AWS. Thinking through how customers engage, you're not just going to be buying compute network and storage and Amazon services. Amazon has become kind of this hub for all types of third-party ecosystems to solve business needs. And it becomes that single point of presence slash billing and operations for a lot of companies that are out there. What this does is it removes the complexity of saying, Not only do we know that MongoDB Atlas and AWS, they work together, but now you can ensure you have one bill, one engagement, one license.It just basically creates an easy wrapper so that customers can transact with these solutions together.

>> I know we're up against the clock. You had something to add?

Mona Chadha

>> Well, no, just going to add to that. I want to give Mongo just a lot of kudos here because Mongo has been one of our partners that really has adopted a lot of our features. And that ranges from things like pay-as-you-go type of pricing options to private offers, to also adopting features like Vendor Insights So Vendor Insights is really an easy way for our end customers to actually be able to acquire compliance documentation around HIPAA, SOC 1, 2, FedRAMP. so that is a huge value to our end customers. I have to say MongoDB does a really amazing job of adopting the buyer features and capabilities so that it makes it easier for the end customers to procure through the Marketplace. So they get the added benefit of speed of procurement acceleration, and then the end customer gets everything that they need all in one spot and in however they want to transact. So it's a real benefit to our end customers.

>> And MongoDB also didn't resist cloud. New you had to go cloud native. Atlas was a game changer for the company and your customers. And so my last... I know we're up against the clock. I want to talk about gen AI adoption, what you guys are seeing. Survey data that we do with our partners, ETR, New York based basically shows this types of activities and use cases today, I'll call them very chatty. They're very ChatGPT And so the real interesting harder use cases that are going to be... There's ROI today, don't get me wrong, but the big value is still not there. The big two... There's examples, you guys gave some this morning, but they're not like at scale yet. So what you guys seeing and what's your expectation for gen AI adoption beyond some of those lighter weight applications?

Mona Chadha

>> Yeah. Look, I think it's still very early. Customers, like we just said, they need help getting started. So what I anticipate is that more and more industries are going to leverage generative AI in very unique ways. And these are industries across financial services, healthcare, retail. It's going to go beyond the chatbot. And we're already seeing very innovative ways in which customers today are using generative AI and things like... Even figuring out, how do you boost your employeesproductivity? That's always a thing. But what they're doing is actually creating things like behavioral models. How do you sort of match up managers with your teams? How do you get your teams to become more efficient? So this is like psychology, right? And so you're starting to see very interesting approaches, but there's going to be more to come. I think the future really is in getting the data right. And what you'll see is just better models, better collection of data and weeding out all of the data that's not good. And that's going to prevent a model from actually coming out with a good outcome. So I think that's going to get better. I think overall technology is going to get better. So this is why AWS has invested in chipsets in our technology, so that models are just going to get faster, better, more reliable, more trustworthy. And as that happens, your compute power is going to have to get more powerful as well. So I think all of those things is what we're going to see more of. So I'm very excited and I'm very excited about working with you guys are investing.

Mona Chadha

>> Yes.

>> Keep up

>> Peder, I know you got to go, but we want to give you the last word on the relationship and also MongoDB.local and what's next. No,

Peder Ulander

>> So I mean, this is the first stop across 23 cities around the globe. We're bringing gen AI to the world, helping developers get started quickly. So we're really excited about the success here in New York. Thank you again for joining us, but the ability for us to get this in the hands of the developers has been absolutely key. And to the point of where we are in the gen AI movement, it's early. It's about enablement, it's about exploration, it's about helping customers understand where to get started. There's no better way to do that than leverage these local series to get your developers in front of the experts with all of the partner ecosystem tools and technologies that you need to move forward. So that's why we're really happy about this program.

>> Well, we're happy you Thank you so much for having us here.

Mona Chadha

>> Thank you.

>> guys out on 23 cities, you're going to be in all 23 cities. Do you have an LLM that replicate

Mona Chadha

>> I know that's right.

Peder Ulander

>> Wouldn't

Peder Ulander

>> We actually know it's fun. We've committed to our execs. We go to about four or five each. So we'll go out and we keynote. So it brings the execs also out into the field where our customers are, and we're not allowed to do the same ones we did last year, so we go meet new folks every time. This year, I have a tour in India and Southeast Asia. So it'll be good.

>> Oh, fantastic. All right. Thanks again, you guys really.

Mona Chadha

>> Well, thank you so much.

>> All right. Keep watching. We'll be right back right after this short break. MongoDB.local live from New York City, watching theCUBE.

Peder Ulander | MongoDB & Mona Chadha | AWS

Peder Ulander

>> Thanks for having us here.

>> You guys both been on theCUBE before.

Mona Chadha

>> Yes.

>> Mona, what's happening in your world? Tell us about your role. Let's start there.

Mona Chadha

>> Like So you're a trusted part. Okay, so what's your angle here?

Peder Ulander

Mona Chadha

>> Over 200 services, yes.

Peder Ulander

>> That integration is key. It's real engineering work. And now you also announced that your GA and Bedrock, what does that mean? What's specifically?

Peder Ulander

>> So there's synergies there.

Peder Ulander

>> So there's ideas in there, and there's also package solutions-

Mona Chadha

>> Blueprint type of solutions, yeah.

Peder Ulander

>> I know we're up against the clock. You had something to add?

Mona Chadha

>> Yes.

>> Keep up

>> Peder, I know you got to go, but we want to give you the last word on the relationship and also MongoDB.local and what's next. No,

Peder Ulander

>> Well, we're happy you Thank you so much for having us here.

Mona Chadha

>> Thank you.

>> guys out on 23 cities, you're going to be in all 23 cities. Do you have an LLM that replicate

Mona Chadha

>> I know that's right.

Peder Ulander

>> Wouldn't

Peder Ulander

>> Oh, fantastic. All right. Thanks again, you guys really.

Mona Chadha

>> Well, thank you so much.

>> All right. Keep watching. We'll be right back right after this short break. MongoDB.local live from New York City, watching theCUBE.