← The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
#732: Using AI to see video content with Meenal Nalwaya, Reka
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- [00:00]
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If you love podcasts, and obviously you do, you need to check out Castro. It's a podcast player designed for people who subscribe to a lot of shows but don't have time to listen to everything. Castro helps you cut through the noise, manage your shows and simply enjoy listening. It's the podcast player built for podcast enthusiasts. So download Castro and start listening today. That's Castro. C A S T R O Enjoy listening the Agile Brand.
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B
Foreign.
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A
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 Build 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. 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. Now onto the show. This episode is brought to you by Rekka, a developer of industry leading multimodal AI models that enable individuals and organizations deploy generative AI applications. Agility requires brands to utilize technology like AI in new and innovative ways to better understand information and interact with their customers, giving them what they want, when, where and how they want it. To help me discuss this topic and some of the recent announcements from Reka, I'd like to welcome Meenal Nawaya, Head of Product at Reka. Meenal, welcome to the show.
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B
Greg, Great to be here.
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A
Yeah, looking forward to talking about this with you. Before we dive in, why don't you tell us a little bit about your background and what brought you to wreck.
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B
Absolutely. Well, I've spent nearly the past decade of my career, you know, across Amazon and Meta focusing on converting really advanced technologies into products that are used by millions and billions of people across the world. And at Meta, in my last stint I worked on multimodal reasoning models for Lama and in Meta AI. And at that point it kind of became clear to me that AI isn't just about bigger models, it's really about building solutions that are solving real world problems. I also clearly saw a gap where while most of the world's data is visual and audio and which is how humans see the world as well, most of the AI that was being built was around text. And that's where I saw an opportunity and I got and I jumped ship and joined reka.
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A
Yeah, yeah, I love it. Yeah. And definitely agree. I'm fascinated with this topic, so looking forward to learning a little bit more. And maybe for those that are not familiar with Reka, I know we've had a few episodes here with people from Wreck up, but for those that are less familiar, can you talk a little bit about what it is and what makes it different?
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B
Absolutely. So at Trekka, we're really building the Enterprise standard for multimodal agents. And we are a full stack multimodal model as well as product company. And our differentiation here really comes from two key pillars. First, we are multimodal first. So we build agents that can see, listen and reason across the Enterprise data that most of the AI has actually ignored till now. So if you look at most of the AI adoption that's happening around you, it's really focused around using text data or using or coding has been highly transformational as well. But images and videos have not gotten that sort of love. And our focus is really around multimodal from that perspective. The second pillar is we are a full stack company. So we are not a wrapper company. We don't use other. We don't lean on OpenAI or Gemini's models, but we build our own multimodal foundational models and then package them into solutions that can be used by our customers. This gives us a lot of control over the kind of quality customization and the speed with which we can move because we are not dependent on anybody else's roadmap. And that's kind of fundamental to our company and our product strategy.
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A
Yeah, yeah. And so you've had some exciting launches recently. I'd love to hear some highlights of those. Why don't you talk through some of those?
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B
Yes, yes. Very excited to share those. We have launched two key platform capabilities. First is Reka Vision, which is a platform capability that lets enterprises have a human like understanding of their images and videos. So what this does is it allows you to ask questions and search over your videos and images directly. So for example, you can just say, show me every slam dunk from last night and it will instantly generate a highlight read for you. I believe, Greg, you have also tried some of our. Or as a security person, you can say, find me all security events this week and generate a report for me. Something that security officers don't want to do because it's very time consuming for them. And it will find all of the relevant clips and it will generate a structured log for you for any of your compliance purposes so that you can really focus on what you do best. The second platform capability we launched is Reka Research which adds a reasoning layer on top of this. So now we can go beyond search and conduct deep research not on all of your private enterprise data as well as across web. So really build that agentic component. It provides structured and sighted answers so that your team can really just go and trace back any of the output and really have this transparency and trust element built into it. So for example, you can ask what themes are trending this season versus last year and we'll give you a boardroom ready report with all the citations that you can go back and check on. So together if you combine vision and research as horizontal platform capabilities, it kind of brings together the perception side of the world and then adds the reasoning layer on top of that, which are sort of the building blocks for multimodal agents in any industry.
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A
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B
Yes, Given that multimodal is really our key pillar of product strategy, we really focus on industries where unlocking this multimodal data is critical. One of these industries is security. In security industry you can imagine we can imagine multiple hundreds of cameras and a large amount of security footage that these officers are overwhelmed with analyzing and looking through. So for example, we worked with the Ohio Police Department where we implemented REKA solutions across more than hundred intersections that they have. And now with these RECA powered agents they are able to achieve 65% faster case resolution and 42% reduction in crime. That is crazy amount of improvement in safety and speed of resolution which I don't think any other tech can achieve at this pace. And this wasn't just about cool tech for us. It was also about solving a real workflow bottleneck and delivering safety for all of the citizens. So as police Officers, the response we hear from them is this allows them to really save time. They have achieved 40% savings in officers time so that these officers can really do their job and not spend time finding the right clip and creating that report and doing compliance. Another example I would love to give is media as an industry media. As you can imagine, the content studios and broadcasters have huge archives of videos that are sitting around kind of, you know, many, many years of content that's there. But it's very hard for them to search and find any relevant footage. And then if you can't find it, you can't repurpose it, you can't repackage it and you can't monetize it. Now, with Rekha's platform, a media company, for example Paramount, can transform its business in multiple different ways. For example, one, when it comes to licensing, they might have decades of content sitting in archives. And now with our human like video understanding, they can make every scene searchable at the scene, theme, actor, even emotion level. And now if you can search and discover footage faster, find me every time Brad Pitt was shown in a video, you can license the content a lot more efficiently. And not only that, I think this can also transform how content is discovered across the partner platforms. So for example, if Paramount licenses this content to partners, let's say it gives it to Netflix, then Reka can drastically just change how the discovery of this content works. Now that you have such rich metadata associated with this content, it will be much easier even for the consumers on these platforms to find content. And then what better discovery means more engagement with the content and you just get more bang for your buck and all of your licensing deals. For example, imagine on Netflix, instead of just searching Find me a romantic comedy, which I think is a pain point all of us have, when we have spent many hours looking for the content we want to watch. You can just search for show me a romantic comedy from the 1960s with a happy ending and actually find something exactly that.
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A
Yeah.
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So I think overall, just more easier discovery means more streaming hours for this content and just higher licensing value for a company like Paramount.
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Yeah.
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Another way this can be used is repurposing this content. We have tools for repackaging this existing content into new formats as well. So for example, if you are a news media company, you will typically be under time crunch because there will be a lot of breaking news which you need to repurpose for different platforms. Now using our Rekka Re generation product, you can instantly create a compilation of all of the news highlights that happened in a day and just share it on different platforms, including social media platforms, where a lot of your audience might be. And as a result, this generates this new audience engagement on different platforms very, very quickly and without adding any additional production costs for you. And then I think one of the key things to call out here is that time is of essence in these industries. If I am a news publisher, if it's about sports highlights, I don't want to spend another week with content editors editing this and then sharing in platforms. It's kind of pointless at that point. So that's where having, using Rekha's Reels generation product, you can simply prompt it to generate, instantly generate all of these compilations that you can share on social media platforms.
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A
Yeah.
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Last, I would also say that now as a publisher, you can increase your advertising and sponsorship revenue because now you can measure your ROI much better and you can sell premium ad slots as well. So, for example, if Coca Cola is advertising with Paramount, Paramount can prove ROI much better by measuring every logo appearance, especially every logo appearance that might happen in a video, for example, in a sports studio, there might be Coca Cola banners behind. It can now track every time Coca Cola is mentioned or Coca Cola appears and then charge and prove the ROI to its advertisers. It can also sell premium placements like it can sell moments of excitement. For example, Nike can decide to only show their ads when there is a moment of excitement, like a goal or something where which they know is likely to make someone buy a shoe. And this is a very premium ad placement for these publishers. And I think that's just some of the ways now being able to sell these premium ad slots and just being able to prove that ROI and adding it to your sales decks are just some of the ways it can help.
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A
Yeah, I mean, that's a lot of exciting stuff that is now available. I wonder where you're thinking as far as what are you excited about as AI evolves and you know, over the next, let's say five years, you know, what, what do you see shifting.
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It's a very interesting question. Five years is a lifetime, right?
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Right.
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In the world of AI, I see two inevitable shifts happening. One I think is kind of obvious one and the second I would say is slightly more Cherian view that I have from the obvious one. I think the world will move from text to multimodal, which we can imagine that the first round of AI adoption is around text and coding. But then most of the world's data or a large part of the world's Data is how humans perceive world. It's in images, video, audio, and I think the time for that is yet to come. So I think that's going to be to drive the next wave. The second is a slightly contrarian view where I think that companies will from wrappers we will move towards more full stack companies because I think as companies scale it will become more and more critical for them that they own the entire stack and have control over the kind of quality, reliability or even pricing power that they have. Especially when you go deeper and start delivering complex real world use cases. It's not, it's not going to be an ideal scenario if for every safety outcome or for every problem that you have to solve in a media company you are dependent on someone else's roadmap. For example, I saw that firsthand at Meta where we were shipping multimodal and Meta AI and hallucination ended up being a big problem for us and we realized that it was much harder to solve it at the fine tuning layer and we really needed to have it incorporated in the pre training layer itself to drive that improvement. And I think that kind of control is critical.
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A
Yeah, yeah. What advice would you have then? You know, given some of these as well as your other experience, what advice would you have for PMs and AI?
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B
Oh, I love this question because there is so much chatter around PMing and pretty much every job at this point and AI. First of all, I think there have been some very famous statements about how PMing is going to be less relevant, et cetera, et cetera in AI. I actually think this is the best time to be a PM because it's much easier using tools like cursor, et cetera to code. And the value that PMs can really add is the what and the why, which is you still need to define what is it that you need to do and why do you need to do that. And very recently Andrew Ng actually said that I think the right PM to ENG ratio now is actually something like 1pm for every two or three engineers because you can code much easier but then you need to still know what is it that you are trying to do. But anyways, coming to the advice. So first I think I have two advice that I would give for any PM in AI. One, the stack is cool but still anchor on the customer problem. Adoption of your product really lives or dies there. If the AI doesn't fit into a user's problem or it doesn't solve a really, really painful problem, it's just not going to stick, it'll just remain cool tech. And second, from an execution perspective, evals or evaluations in the world of AI are the new pid. So your product will really be defined by the success metric and that measurable outcome in this case is going to be the real customer and the real data and and having very solid set of evals on what good looks like is going to make sure you're building the product in the right direction.
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A
Yeah, yeah. Love it. Well Meenal, thanks so much for joining today. I'd like to thank Meenal Nawaya, Head of Product at Reka, for joining the show. You can learn more about Meenal and Reka by following the links in the show notes. And thank you to our sponsor Reka for supporting the show. Reka is a developer of industry leading multimodal AI models that enable individuals and organizations to deploy generative AI applications. Thanks again for listening to the Agile Brand. 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@theagilebrand.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. The Agile Brand before we continue, I wanted to share a key strategic resource that a majority of the Fortune 500 are already aware of. Finding the best technology, business and talent solutions is not easy. With business demands and competitive pressures mounting, you need to be able to design, deploy and optimize your technology to provide leading customer experiences while driving business growth. Those of you that have been listening to this show for a while know that this podcast is brought to you by Tech Systems, a global provider of technology, business and talent solutions for more than 80% of the Fortune 500, tech systems accelerates business transformation for their customers. Whether you're looking to maximize your technology roi, drive business growth, or or elevate customer experiences, Tech Systems enables enterprises to capitalize on change. Learn more@techsystems.com that's teksystems.com now let's get back to the show.