#652: The power of multimodal AI with Dani Yogatama, Reka

Summary

Podcast Summary: The Agile Brand with Greg Kihlström®
Episode #652: The Power of Multimodal AI with Dani Yogatama, Reka
Release Date: March 19, 2025

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Introduction

In episode #652 of The Agile Brand, host Greg Kihlström engages in an insightful conversation with Dani Yogatama, CEO and Co-Founder of Reka. The episode delves into the transformative potential of multimodal AI in the enterprise sector, exploring how businesses can effectively integrate advanced AI technologies to enhance productivity and drive growth.

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1. Guest Background: Dani Yogatama and Reka

Danny Yogatama’s Journey

Danny Yogatama introduces himself at [03:02] with a compelling background: “I grew up in Indonesia, went to grad school, received my PhD from Carnegie Mellon. Prior to Reka, I worked for seven years at DeepMind in London. My academic research focuses on multimodal models, memory systems, and reinforcement learning.” His extensive experience in AI research and development sets a strong foundation for Reka's innovative endeavors.

Founding Reka

At [03:46], Danny explains the inspiration behind Reka:
“We started Reka because we believe AI has the power to transform the world but only if it's built and applied in the right way. My goal has always been to ensure that this technology benefits as many people as possible, goes beyond research labs or big corporations, and is helpful for everyone in the world.”

Danny emphasizes the transition from research to practical application, highlighting the readiness of AI for mass adoption as a pivotal reason for founding Reka.

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2. The Power of Multimodal AI in the Enterprise

Defining Multimodal AI

Greg kicks off the discussion at [01:11], focusing on the significance of multimodal AI. Multimodal AI refers to systems that can process and integrate multiple forms of data inputs—such as text, images, audio, and video—to provide comprehensive and intelligent insights.

Reka’s Multimodal Models

At [04:57], Danny details Reka’s flagship offerings:
“Our multimodal models, Raka Edge, Flash, and Core, are designed to enhance human productivity. Recently, we launched RekkaFlash 3, a 21 billion parameter model optimized for speed, efficiency, and quality. It competes with proprietary models like OpenAI's, offering developers and researchers a powerful yet lightweight tool.”

Enterprise Intelligence Platform: Nexus

Danny introduces Nexus at [06:00]:
“Nexus is a multimodal enterprise intelligence platform that focuses on creating and managing AI workers. These AI workers handle repetitive tasks—such as conducting topic research, processing invoices, generating sales leads—allowing human employees to concentrate on creative and strategic work.”

Capabilities of AI Workers

Nexus workers possess diverse capabilities, including browsing the web, searching internal files, writing and executing code, and analyzing various multimodal data sources like PDFs, audio recordings, and images. This partnership between humans and AI workers significantly boosts enterprise efficiency and productivity.

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3. Common Mistakes in AI Implementation by Companies

At [07:43], Danny addresses the pitfalls organizations often encounter when adopting AI:

1. Reliance on Off-the-Shelf Models:
   “A common mistake is relying solely on off-the-shelf AI models without customization. Every organization has unique challenges and constraints, and a one-size-fits-all approach often fails to deliver real value.”

2. Lack of Integration:
   “Organizations should adopt models that can integrate seamlessly with their existing systems and internal data to maximize effectiveness.”

3. Limited Functionality:
   “AI should not just generate text outputs but also perform meaningful actions. Previous-generation models that function solely as chatbots fall short of expectations. AI needs to accomplish tasks to add real value.”

Danny emphasizes the importance of customizing AI solutions to fit specific business needs and ensuring that AI systems are capable of performing actionable tasks beyond mere data generation.

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4. What Sets Reka Apart in the AI Landscape

At [12:37], Danny highlights Reka’s unique position in the competitive AI market:

1. Full Stack Company:
   “We are a full stack company that not only develops our own internal models but also builds products. This dual expertise allows us to deliver comprehensive AI solutions.”

2. Cost Efficiency:
   “As a lean startup with modest resources, our focus has always been on cost efficiency. Our models, like RekkaFlash 3, are developed with significantly lower budgets compared to competitors, making state-of-the-art AI accessible and affordable.”

3. Control and Customization:
   “Reka offers enterprises the ability to control the deployment process, choosing between using their own servers or ours. This ensures higher robustness and reliability, particularly for applications sensitive to downtime.”

Danny underscores how Reka’s emphasis on cost-effective, customizable, and controllable AI solutions differentiates them from larger, less flexible competitors.

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5. Measuring Success in AI Implementation

At [14:00], Greg prompts a discussion on metrics for evaluating AI success. Danny outlines a multifaceted approach to measuring ROI:

1. Cost Reduction:
   Utilizing AI to lower operational costs.

2. Customer Satisfaction:
   Improving the customer experience through efficient AI applications.

3. Operational Metrics:

   • Latency and Uptime: Ensuring AI systems are responsive and consistently available.
   • Robustness: Minimizing downtime and ensuring reliability, especially for critical business applications.

Danny emphasizes that beyond model performance, businesses should assess how AI integration affects overall operational efficiency and user satisfaction.

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6. Future Developments and Reka's Roadmap

At [16:55], Danny shares Reka’s vision for the future:

1. Agentic Era of AI:
   2025 marks the beginning of the "agentic era," where AI agents are expected to perform more complex and autonomous tasks.

2. Enhanced Multimodal Reasoning:
   Continuous improvement in multimodal reasoning to ensure AI agents are truly effective in assisting with business operations.

3. New Product Launch - Guardian:
   “Guardian is a video monitoring solution focused on real-time threat detection. It leverages our proprietary models and multimodal capabilities to provide advanced security monitoring.”

Danny anticipates that businesses will increasingly adopt AI in production environments, recognizing its tangible benefits and the decreasing costs of developing high-performance models.

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7. Staying Agile in the AI Industry

In the final segment at [19:42], Greg asks Danny how he maintains agility in his role. Danny attributes Reka’s agility to:

1. Strategic Foresight and Adaptability:
   Staying ahead of technological advancements and being ready to pivot as needed.

2. Strong Feedback Loops:
   Incorporating feedback from internal teams, partners, customers, and the broader AI community to continuously refine and improve their offerings.

3. Empowered Team Culture:
   “A team that is highly empowered, has a sense of ownership and trust, will help us succeed. That is what our team culture is at Reka.”

Danny emphasizes that a cohesive and motivated team is crucial for maintaining agility and responding effectively to the rapidly evolving AI landscape.

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Conclusion

Greg concludes the episode by thanking Danny Yogatama for his insightful contributions. Listeners are encouraged to explore more about Reka and Danny through the show’s provided links. The episode underscores the importance of integrating multimodal AI thoughtfully and strategically to unlock significant business value, highlighting Reka’s role in making advanced AI accessible and practical for enterprises.

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Notable Quotes

• Danny Yogatama [03:46]:
  “We started Reka because we believe AI has the power to transform the world but only if it's built and applied in the right way.”

• Danny Yogatama [07:43]:
  “A common mistake is relying solely on off-the-shelf AI models without customization. Every organization has unique challenges and constraints.”

• Danny Yogatama [12:37]:
  “As a lean startup with modest resources, our focus has always been on cost efficiency. Our models are developed with significantly lower budgets compared to competitors.”

• Danny Yogatama [14:00]:
  “The ROI of implementing AI technology is actually multifaceted. From cost reduction to improving customer satisfaction, it’s essential to evaluate multiple metrics.”

• Danny Yogatama [19:42]:
  “Staying agile requires a combination of strategic foresight, adaptability, and a strong feedback loop. Our team’s sense of ownership and trust is crucial.”

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Further Information

To learn more about Danny Yogatama and Reka, listeners can follow the links provided in the show notes. For additional episodes and insights on marketing technology, AI, and customer experience, subscribe to The Agile Brand and visit theagilebrand.com.

Transcript

[Greg Kilstrom]

We all know data is valuable. We use it to tell a story to make informed decisions for our businesses. But turning data into actionable insights can be a challenge. It's time to unlock the true potential of your business data with Domo's AI and Data Products platform. Domo lets you channel AI and data into innovative uses that deliver a measurable impact. Ask your data Anything at any time. Anyone on your team can use Domo to easily prepare, analyze, visualize, automate and distribute data, all amplified by AI. Domo goes beyond productivity. It's designed to transform your processes, helping you make smarter and faster decisions and drive real growth. All powered by Domo's trust, flexibility and years of expertise in data and AI innovation. Data is hard. Domo is easy. Make smarter decisions and propel your business forward with Domo. Learn more today@AI that's AI.domo.com the Agile.

[Danny Yogatama]

Brand.

[Greg Kilstrom]

Welcome to season seven of the Agile Brand where we discuss the trends and topics marketing leaders need to know. Stay curious, stay agile and join the top enterprise brands and Martech platforms as we explore marketing technology, AI, E commerce and whatever's next for the Omnichannel customer experience. Together we'll discover what it takes to create an agile brand built for today and tomorrow and built for customers, employees and continued business growth. I'm your host Greg Kilstrom, advising Fortune 1000 brands on martech, AI and marketing operations. The Agile Brand podcast is brought to you by Tech Systems, an industry leader in full stack technology services, talent services and real world application. For more information go to teksystems.com to make sure you always get the latest episodes, please hit subscribe on the app you listen to podcasts on and leave us a rating so others can find us as well. And now onto the show. Is your organization just jumping on the AI bandwagon or do you have a solution that will support your company's needs in the short and long term? Welcome to this episode brought to you by Reca, a developer of industry leading multimodal AI models that enable individuals and organizations to deploy generative AI applications. Today we're going to talk about the power of multimodal AI in the enterprise and why it's important for businesses to incorporate AI that is able to utilize multiple input sources, multiple languages and flexible contexts to provide more intelligent insights. To help me discuss this topic, I'd like to welcome Danny Yogatama, CEO of ReCA. Danny, welcome to the show.

[Danny Yogatama]

Hello everyone. Great to be here today.

[Greg Kilstrom]

Yeah, looking forward to talking about this with you. Before we dive into the topic though, why don't you start by giving a little background on yourself and your role at wreka.

[Danny Yogatama]

Yeah. I'm Danny Yogatama, CEO and co founder of wreka. I grew up in Indonesia, went to grad school, received my PhD from Carnegie Mellon. Prior to RECA, I worked for seven years at DeepMind in London. My academic research focuses on multimodal models, memory systems and reinforcement learning.

[Greg Kilstrom]

Great, let's dive in here. Why don't we start with some background on RECA and what makes it unique. There's a lot of talk about AI and generative AI in particular of late. Can you talk about what inspired you to co found Reka?

[Danny Yogatama]

Yeah. We started Reka because we believe AI has the power to transform the world but only if it's built and applied in the right way. My goal has always been to ensure that this technology benefits as many people as possible compared goes beyond research labs or big corporations but be helpful for everyone in the world. Reka is our vehicle to create the highest impact where we could push the boundaries of AI while making it accessible and practical for real world use. But yeah, I started the company after working for about 15 years doing research on a personal level. So after spending so many years doing research I also felt like I wanted to try something different. Wanted a new challenge and and about like two years ago I felt that the timing was right, the technology got to a place where it is ready for mass adoption. So yeah, excited to be doing this with a few friends.

[Greg Kilstrom]

Yeah, yeah definitely. And so can you talk a little bit about what are some of the types of problems or challenges that Reka solves for.

[Danny Yogatama]

Yeah. So our goal is to use AI to improve human productivity by by developing models and agentic platforms. Most people probably know us Rekka from our multimodal models Raca Edge, Flash and Core. We open source a new model third generation of Raca Flash. We call it RekkaFlash 3. It is the most performant model of its size. We just did it a few days ago. It is a 21 billion parameter general purpose model optimized for speed, efficiency and quality. It is competitive with proprietary models such as OpenAI01. Mini Raca Flask is a great model for developers and researchers that need a powerful but lightweight model to build on. But yeah, so in addition to models we also build platforms applications that is powered by these models. One of our flagship platform is called Nexus. This is a multimodal enterprise intelligence platform focusing more on creation and organization management of AI workers. So we spend a significant portion of our time on repetitive tasks, limiting our ability to focus on creative and strategic work as like humans. Right. So Nexus actually improves enterprise efficiency and, and increases productivity by enabling humans employees to partner with AI workers which can be customized to specialize in different tasks, for example, conducting topic research, processing invoices, generating sales leads. In this partnership between human employees and AI workers, we as humans can focus on management and delegations managing a bunch of AI workers. While this AI workforce performs like low level repetitive tasks. Our Nexus workers have capabilities to for example, browse the web, search from internal files, write code, execute code, and analyze contents from various multimodal data from PDFs, audio recordings, video databases, images and like. Yeah. And the web as well.

[Greg Kilstrom]

Yeah. So you know, as I mentioned and as you surely know, there's, there's a lot of talk about AI, there's a lot of investment being made in AI by, by companies and yet there's probably a lot of missteps that, that companies could make. What, what do you, what do you see as you know, what do a lot of companies get wrong when incorporating AI into their organizations?

[Danny Yogatama]

Yeah, that's a great, a great question, Greg. So AI has the potential to transform businesses, but many organizations, as you said, struggle with implementation. There are some common mistakes or challenges that I see that slow down AI adoptions. So for example, a common mistake is relying solely on off the shelf AI models without customization. It is important to remember that every organization has unique challenges, unique, unique constraints. And a one size fits all approach often fails to deliver real value. An organization will want to adopt a model that can adapt to their business needs. So this is not just more performant but also more cost efficient so that they can get AI to truly work for them. We develop Nexus, our agentic platform, to allow enterprises to be able to do this really easily. Of course organizations should also look into a model or product that they can put into their existing system integration. So we also built it with a lot of easy integrations for existing internal data that they currently have. In addition to not relying solely on off the shelf models. It is important to remember that AI is not just about generating insights in the form of text outputs. To me it is about accomplishing tasks. So if you see previous generation AI models, chatbots, so you ask a question and then you get a text output. So that's just an insight. I mean that's nice. But I think nowadays people expect AI to do more than that. You want them to actually do stuff for you, not just producing output that be able to do to do stuff for you. So that's what we focus on here at trackar. So many businesses, like, you know, they stop at like just leaving on this like, chatbot version of AI, but don't use it in the right way so that AI can. Can do stuff, sorry, like take meaningful actions, right? So this is what Nexus enables them to do. A major focus for us, building AI that doesn't just, you know, like produce like your textual output. Right? But also like doing stuff for you. It's like automation, delegation. So you could just like, you know, delegate something to them and just forget about it. Like, and then like every once in a while you could check on them. Like how you would work with your regular human employees, right? And then maybe they give you updates every day or every week. However, like, frequently you want to set it up.

[Greg Kilstrom]

We all know data is valuable. We use it to tell a story, to make informed decisions for our businesses. But turning data into actionable insights can be a challenge. It's time to unlock the true potential of your business. Data with Domo's AI and Data Products platform. Domo lets you channel AI and data into innovative uses that deliver a measurable impact. Ask your data. Anything at any time. Anyone on your team can use Domo to easily prepare, analyze, visualize, automate and distribute data, all amplified by AI. Domo goes beyond productivity. It's designed to transform your processes, helping you make smarter and faster decisions and drive real growth. All powered by domo's trust, flexibility and years of expertise in data and AI innovation. Data is hard. DOMO is easy. Make smarter decisions and propel your business forward with Domo. Learn more [e-mail] that's AI.domo.com Want to learn more and join the discussion About Marketing and AI? Attend a premier conference dedicated to marketing and AI. That's Meacon, the Marketing Artificial Intelligence Conference. From October 14 through 16 in Cleveland, Ohio. MEACON brings together the brightest minds and leading voices in AI. Don't miss this opportunity to connect with a dynamic community of experts, visionaries and enthusiasts. The Agile brand is proud to be the lead media sponsor of this important event. Register today@marketingai institute.com that's marketing AI institute.com and use the code AGILE150 for $150 off your registration fee. I can't wait to see you there. And so I know you've touched on a few different points as you've talked through some of these things, but what would you say sets Reka apart from its competitors? In the AI landscape.

[Danny Yogatama]

Yeah, yeah. So there's a lot of companies in AI, Obviously nowadays we are different because we are a full stack company that not only develops our own internal models, but also built products. But within, like among companies that develop their own models, we are very different because we are a lean startup with modest resources. So as such, our focus from the beginning of the company has always been on cost efficiency. So including when we're developing our models or that power our platforms. Right. As a full stack company that has the expertise to both train models and develop applications products, we are I think well positioned to deliver the highest value for our customers. So for example, our technology allows us to develop AI models that only cost about like five to million dollars and they perform competitively with like models from other companies that are chained with like tens or even hundreds of millions of dollars. So for our customers it means that they have access to secure, cost efficient, state of the art AI.

[Greg Kilstrom]

Yeah, yeah. So how should, so I mean you've mentioned efficiency and cost and things like that. How should companies be measuring their success in implementing AI in their organization?

[Danny Yogatama]

Yeah, yeah. The ROI of implementing AI technology is actually multifaceted. Right. So from cost reduction, like using AI to reduce your operational costs, but also to improve customer satisfaction. But this requires organizations, businesses to not only look at just the model performance, but also things like latency, operational uptime, how many hours are the model available for, you don't want to deploy it. And then there are periods of downtime because the provider server is like, you know, not available because like the traffic is too high or something like that. So I think like time is also important in addition to that, also robustness to like failures. Right. At the end of the day, I think we want to make sure that business users are happy and satisfied with the whole experience and that they are confident when working together with our AI.

[Greg Kilstrom]

Yeah, well, and I would say the uptime probably has a different, it has an additional meaning when you have agents that are, to your, to what you were saying earlier, when they're performing tasks, you know, semi autonomously or autonomously. Uptime means it, it would be the equivalent of your, your human employees not having access to the Internet or something. Right. So I mean that's some of these metrics that you mentioned how take on some, some different meanings for your customers. Would you say that's true?

[Danny Yogatama]

Yeah, 100% that is correct. And it is also one of the things. So when businesses work with us, they control the entire deployment process. They can choose whether they want to use Their own server, our server, depending on what is the most suitable for them. If they work with companies that only offer data models behind API, obviously they cannot control when the API is down because of some other reasons. You just, you know, hope that they fix it as soon as possible. And there's a lot of like applications of this technology that is very sensitive to like, you know, you just like it's so critical to businesses that you just cannot afford to have it down like. But so by like, you know, working with us, being able to deploy and control the deployment yourself, you're guaranteed to have like higher robustness to like, you know, server failures because you control everything. There's not going to be traffic from other companies that are, you know, like eating away some of your like bandwidth today.

[Greg Kilstrom]

Yeah, definitely. So let's talk about what's coming soon as well. Certainly as someone who's done a lot of research and as Reka's built a lot of innovative tools already, what do you see as what should companies be looking out for in their AI in the months to come? And maybe what's on Rekka's radar as well?

[Danny Yogatama]

Yeah, no, I think 2025, everybody knows, is the agentic era in AI where people start to expect more, more. I expect there's a lot of movements in this space. I think for us right from the beginning our focus has always been on multimodal reasoning. I think these two are key components to make agents that actually work. Not just I say I have something but it doesn't actually help you with your sauce outreach 100% of the time. And also I think this is an exciting time where AI models started to actually, it's not like maybe from last year being deployed in production to solve many real world problems. People have understood now that this technology actually helps their businesses. It's not just like an initial testing period. I have passed people. Oh, I actually get a lot of values from this. They started deploying it in production. So I think that is exciting for us. And then a lot of companies also now realize that adopting this technology and even pushing it further doesn't necessarily require massive budgets. You don't have to spend so much money to be able to benefit from this technology. And it can be used in a cost efficient way so they get the best return of investment. And the cost of developing this model also continues to go down as we have shown with our recent launch of like Reka Flash 3, our latest model, most performant multimodal reasoning model of its size. But yeah, so I think what's coming up for us is we have this enterprise intelligence platform, Nexus for creating and managing AI workers. We are continuing to build multimodal agentic platform. We have another product called Guardian that's going to be launched publicly very soon in the next few weeks. It's a video monitoring solution built on top of the same models that we use for Nexus, but focusing more on real time threat detection, more video monitoring software. Both of these products obviously use our proprietary models and multimodal genetic platforms and can be easily integrated into organizational processes. I definitely hope I can share more about Guardian the ways to come.

[Greg Kilstrom]

Yeah, yeah, I'm looking looking forward to learning more about that for sure. Well Danny, thanks so much for joining today. One last question for you before we wrap up here. I like to ask this question to everybody. What do you do to stay agile in your role and how do you find a way to do it consistently?

[Danny Yogatama]

Yeah, it requires I think a combination of strategic foresight, adaptability and a strong feedback loop, both internally within RAKOW and our company, but also externally from our partners, customers and the AI community more broadly. It is a technology that is evolving very rapidly. So for us to keep up with progress as a company, we need to move fast and continuously improve our technology. So staying agile is super imperative. So of course I cannot do this without our team members. A team that's highly empowered, has a sense of ownership and trust, will help us succeed and that is what our team culture is at Trek. Thanks for having me as a guest, Greg. It's great to be here.

[Greg Kilstrom]

Yeah, thanks so much for joining again. I'd like to thank Danny Yogatama, CEO of Reka, for joining the show. You can learn more about Reka and Danny by following the links in the show notes. Thanks again for listening to the Agile Brand brought to you by Tech Systems. If you enjoyed the show, please take a minute to subscribe and leave us a rating so that others can find the show as well. You can access more episodes of the show@theagile brand.com that's theagile brand.com and contact me. If you're interested in consulting or advisory services or are looking for a speaker for your next event, go to www.greggkilstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.

[Danny Yogatama]

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[Greg Kilstrom]

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