#732: Using AI to see video content with Meenal Nalwaya, Reka

Summary

The Agile Brand with Greg Kihlström® #732:
Using AI to See Video Content with Meenal Nalwaya, Reka
Release Date: September 11, 2025

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Episode Overview

This episode tackles the future of artificial intelligence in content discovery and enterprise applications, spotlighting the transformative impact of multimodal AI on how organizations leverage video and image data. Host Greg Kihlström sits down with Meenal Nalwaya, Head of Product at Reka, to discuss Reka’s approach to building AI agents that both understand and reason over visual, audio, and textual enterprise data. Together, they cover recent product launches, tangible industry applications, evolving trends in AI development, and practical advice for PMs and product leaders entering the AI domain.

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Key Discussion Points & Insights

1. Meenal Nalwaya’s Background and Motivation for Joining Reka

[02:35-03:27]

• Meenal’s experience at Amazon and Meta focused on operationalizing advanced technologies for billions of global users.
• At Meta, she worked on multimodal reasoning models (notably with Llama and Meta AI).
• She identified a critical gap: while most human experience and enterprise data is visual and audio-based, most AI advances were concentrated around text.
  • "AI isn't just about bigger models. It's really about building solutions that are solving real world problems." — Meenal Nalwaya [02:52]

2. What Sets Reka Apart in the AI Landscape

[03:49-05:08]

• Reka positions itself as “the enterprise standard for multimodal agents”, integrating full-stack development—building both foundational models and end-user solutions.
• The company's two pillars:
  • Multimodal-first: Agents can “see, listen, and reason” over images, videos, and audio as easily as text.
  • Full Stack Control: Reka builds its own foundational models (not wrapping others’ APIs, e.g., OpenAI or Gemini), creating greater flexibility, customization, and quality assurance.
  • "This gives us a lot of control over the quality, customization and the speed with which we can move..." — Meenal Nalwaya [04:38]

3. Recent Product Launches: Reka Vision & Reka Research

[05:17-07:14]

• Reka Vision:
  • Empowers enterprises to obtain human-like understanding of video and image assets.
  • Enables complex queries over video and images (e.g., "show me every slam dunk from last night").
  • Automates highlight reels, compliance reporting, and security event detection.
    • "It allows you to ask questions and search over your videos and images. Directly." — Meenal Nalwaya [05:31]
• Reka Research:
  • Adds a reasoning layer—conducts deep research over private enterprise or public web data.
  • Generates structured, cited answers and boardroom-ready summary reports.
  • Enhances transparency, trust, and facilitates tracing of results.
• Combined, these capabilities provide “the building blocks for multimodal agents in any industry.”

4. Real-World Industry Applications

[07:20-13:31]

Security

[07:20-09:24]

• Case Study: Ohio Police Department
  • Reka solutions deployed across 100+ intersections:
    • 65% faster case resolution
    • 42% reduction in crime
    • 40% time savings for officers on administrative tasks
  • "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." — Meenal Nalwaya [08:44]

Media & Content

[09:25-12:17]

• Content Discovery & Licensing:
  • Example with Paramount: Decades of video archives become searchable by scene, theme, actor, or emotion; facilitates efficient content licensing.
    • "They can make every scene searchable at the scene, theme, actor, even emotion level ... you can license the content a lot more efficiently." — Meenal Nalwaya [10:07]
• Enhanced Viewer Search:
  • Viewers can request, e.g., "show me a romantic comedy from the 1960s with a happy ending."
• Content Repurposing:
  • Reka Reels: Instantly compiles highlight reels, breaking news, or tailored content for social media and multi-channel distribution.
    • "You can instantly create a compilation of all of the news highlights that happened in a day and just share it on different platforms ... without adding any additional production costs." — Meenal Nalwaya [11:31]
• Advertising & Sponsorship ROI:
  • Precisely measures logo appearances, enables premium ad placements, and ROI proofs for advertisers like Coca-Cola and Nike.
    • "Paramount can prove ROI much better by measuring every logo appearance ..." — Meenal Nalwaya [12:34]

5. The Future of AI: Predictions for the Next Five Years

[13:47-15:38]

• Shift 1: Text to Multimodal
  • Current AI adoption focuses on text and coding, but the next wave will drive AI understanding across images, video, audio—mirroring the complexity of real human perception.
  • "The time for that is yet to come. So I think that's going to be to drive the next wave." — Meenal Nalwaya [14:17]
• Shift 2: Wrapper to Full Stack
  • As use cases become more complex, companies will build and own their AI stack for reliability, control, and pricing.
  • "It'll 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..." — Meenal Nalwaya [14:46]
  • Draws from experience at Meta: top-down integration required to genuinely reduce hallucinations in AI outputs.
    • "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." — Meenal Nalwaya [15:21]

6. Advice for Product Managers and Teams Building with AI

[15:50-17:37]

• Dispels notion that PMs are less relevant in the age of AI.
  • "This is the best time to be a PM..." — Meenal Nalwaya [16:03]
  • Coding is easier with modern tools, meaning PMs must focus on defining the 'what' and 'why.'
  • "The value that PMs can really add is the what and the why..." — [16:06]
  • Andrew Ng cited: ideal PM to engineer ratio is 1:2 or 1:3
• Two Core Principles:
  1. Anchor on true customer problems—AI as a solution must solve real, painful user needs.
     • "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..." — [16:57]
  2. Build strong evaluation (evals): Success metrics and real data outcomes are paramount—evaluations define product direction and impact.

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Notable Quotes & Memorable Moments

• "AI isn't just about bigger models. It's really about building solutions that are solving real world problems."
  – Meenal Nalwaya, [02:52]

• "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."
  – Meenal Nalwaya, [03:58]

• "This gives us a lot of control over the quality, customization and the speed with which we can move because we are not dependent on anybody else's roadmap."
  – Meenal Nalwaya, [04:38]

• "You can just say 'show me every slam dunk from last night' and it will instantly generate a highlight reel for you."
  – Meenal Nalwaya, [05:33]

• "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."
  – Meenal Nalwaya, [08:44]

• "Instead of just searching 'Find me a romantic comedy'... You can just search for 'show me a romantic comedy from the 1960s with a happy ending' and actually find something. Exactly that."
  – Meenal Nalwaya, [11:07]

• "I think the world will move from text to multimodal... The time for that is yet to come."
  – Meenal Nalwaya, [14:17]

• "As companies scale, it'll become more and more critical for them that they own the entire stack... For example, I saw that firsthand at Meta..."
  – Meenal Nalwaya, [14:46]

• "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."
  – Meenal Nalwaya, [16:06]

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Timestamps for Important Segments

• [02:35] Meenal’s professional history and motivation
• [03:49] Reka's company overview and differentiation
• [05:17] Launch of Reka Vision & Reka Research
• [07:20] Security industry case study (Ohio Police Dept.)
• [09:25] Application in media, content discovery, and advertising
• [13:47] Future outlook: Multimodal and full stack AI shifts
• [15:50] Advice for PMs and product teams in AI

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Takeaways

• Reka’s approach empowers enterprises to harness the full spectrum of their data—not just text, but images, video, and audio—resulting in more efficient workflows, better customer experiences, and greater ROI.
• The next frontier in AI will be genuinely multimodal and led by organizations committed to owning and refining their own foundational technologies.
• Product leaders should focus on real user problems and implement rigorous metric-driven development to ensure AI delivers tangible, valuable outcomes.

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For more, visit theagilebrand.com or the show notes for links to Meenal and Reka.

Transcript

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[Greg Kilstrom]

Foreign. 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. 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 Reka, a developer of industry leading multimodal AI models that enable individuals and organizations to 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 wrka. Meenal, welcome to the show.

[Meenal Nawaya]

Greg, Great to be here.

[Greg Kilstrom]

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 Reka.

[Meenal Nawaya]

Absolutely. Well, I've spent nearly the past decade of my career across Amazon and Meta focusing on converting really advanced technologies into products that are used by millions and billions of people across across the world. And at Meta, in my last stint I worked on multimodal reasoning models For Llama 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 air 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.

[Greg Kilstrom]

Yeah. Yeah, I love it. Yeah. And definitely agree. I'm, I'm, I'm fascinated with this, this topic. So looking forward to, to learning a little bit more. And maybe for those that are not familiar with Wrecker, I know we've had a, we've had a few episodes here with, 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?

[Meenal Nawaya]

Absolutely. So at Reka, 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. We are not a wrapper company. 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 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.

[Greg Kilstrom]

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?

[Meenal Nawaya]

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 you can, 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 generate all of the, 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 RECA 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 cited 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 perceptions 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.

[Greg Kilstrom]

I wonder if you could give us maybe a real world example of this stuff in action.

[Meenal Nawaya]

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 there is, you 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 RECA solutions across more than 100 intersections that they have. And now with these rekha 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.

[Greg Kilstrom]

Yeah.

[Meenal Nawaya]

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.

[Greg Kilstrom]

Yeah.

[Meenal Nawaya]

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 Reka Reels 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 platforms. It's kind of pointless at that point. So that's where having. And 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.

[Greg Kilstrom]

Yeah.

[Meenal Nawaya]

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. 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 like 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.

[Greg Kilstrom]

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 over the next, let's say five years, what do you see shifting?

[Meenal Nawaya]

It's a very interesting question. Five years is a lifetime. 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 as companies scale it'll 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 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.

[Greg Kilstrom]

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?

[Meenal Nawaya]

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 at the new pid. So it's your 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 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.

[Greg Kilstrom]

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 Rekka 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 [e-mail] 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.gregkillstrom.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.

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