How Dresma Hit $2M ARR With Usage-Based Pricing & AI-Powered E-Commerce Imagery

Summary

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Episode Overview

Title: How Dresma Hit $2M ARR With Usage-Based Pricing & AI-Powered E-Commerce Imagery
Guest: Siddharth Sinha (Co-founder & CEO, Dresma)
Host: Nathan Latka
Date: January 29, 2026

Nathan Latka interviews Siddharth Sinha, CEO and co-founder of Dresma, an AI-powered SaaS platform transforming e-commerce visual content creation. In just five years since launch, Dresma hit $2M in ARR by leveraging a unique usage-based pricing strategy, deep AI integration, strong studio partnerships, and a capital-efficient India-based team. This episode dives into product mechanics, growth strategies, pricing model, team structure, tech stack, fundraising, and market outlook.

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Key Discussion Points & Insights

Dresma’s Mission and Product Offering

• What Dresma Does:

  • Helps brands create all content for their online presence—across marketplaces, social media, and web stores. Outputs include videos, lifestyle imagery, and PDP (Product Detail Page) content, generated at studio quality and at scale.
  • “Think of us as a marketing agency on steroids. We give you all of the intelligence that an agency gives you about your brand, your environment, and the landscape, as well as workflows to create content that makes you successful.”
    — Siddharth Sinha [01:41]

• AI Technology Stack:

  • Built primarily on Google Gemini for image and content generation; various video models are also leveraged depending on the use-case.
  • A proprietary data layer powers real-time intelligence and prompts, informing both AI model output and brand content strategy.
  • “We lay a data foundation below [Gemini] so that… the model can be best prompted to create content for that particular brand.”
    — Siddharth Sinha [02:54]

• Example Customer Use Case (Puma):

  • Dresma localized European content for Puma’s Southeast Asian launch, helping select appropriate models, locations, and product contexts based on data-driven insights.
  • “All of it was done using AI: AI models, AI locations, and essentially localized the entire product portfolio for that market.”
    — Siddharth Sinha [02:09]

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Pricing Model & Customer Value

• Usage-Based Pricing:

  • No seat-based upsell; charges solely depend on the amount of content customers create (“there’s no cost to the platform itself, just the content you’re creating”).
  • Credits are dollar-matched: $1 = 1 credit, with volume discounts at high consumption levels ($200K+ per year).
  • Average annual contract value is $60,000. Largest customer pays $500,000/year.
    — (Multiple, [00:02], [06:35])

• Why Customers Pay:

  • Value is in both the data-driven content recommendations and the highly customized imagery outputs for each market and channel.
  • “What the brand is also paying us for are two things: the data layer itself…and the content creation layer.”
    — Siddharth Sinha [03:41]

• LLM Parsing Costs:

  • 25-30% of total revenue goes toward Gemini credits; the rest is value-add (data, workflow, recommendations).
  • “That’s not bad.”
    — Nathan Latka [03:39]

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Go-To-Market (GTM) and Growth Strategy

Partnerships with Studios

• Channel Revenue:
  • ~50-55% of revenue comes via studio partnerships in Western Europe, the US, and globally.
  • Studios handle original product photography and Dresma transforms those images into videos, lifestyle content, etc.:
    • “The initial photography is done by ePhoto [Italy], then they use our workflows to take those flat lay shoots and convert them into model images, videos, lifestyle imagery…”
      — Siddharth Sinha [10:56]
    • “Currently about, I think, 50 or 55% of our revenue comes from that channel.”
      — [12:11]

Lead Generation via Free Tools & SEO

• Programmatic SEO:
  • Dresma uses free utility tools (“HD photo converter” brings in nearly 50% of web traffic), driving ~4,300 leads/month.
  • Intention is to let customers test technology, build trust, and convert to paid tiers rapidly.
    • “It allows the customer to have a small foot in our door… These are typically small wins marketing or studio teams look for.”
      — Siddharth Sinha [14:01]

Outbound/Account-Based Marketing (ABM)

• Tech Stack for ABM:

  • Smartlead (sequencing and outreach)
  • Apollo (data source)
  • Clay (data enrichment)
  • In-house LinkedIn automation/orchestration tools
    — [15:46]

• Results from ABM:

  • 30-35% of new revenue in the last year came from these outbound/ABM efforts.

Team Structure

• Lean India-Based Team:
  • 31 employees total, with 5 in sales/marketing—2 AEs (Account Executives, no SDRs), and ~3 in marketing.
  • AEs have quota of $0.5–0.75M and are paid average of $20,000 base (India-based), plus commission.
  • “You can have people based in India sell to large enterprise US customers. You do need some face time…”
    — Siddharth Sinha [18:59]

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Startup Economics & Fundraising

• Revenue Growth:

  • Dec 2024 ARR: $1.3M
  • Dec 2025 ARR: $2M (28 customers)
  • Largest customer: $0.5M/yr.

• Capital Raised:

  • $3M in seed funding (end of 2021, $10M post-money, with $400–450K revenue at the time).
  • “At that time, we did have revenue—book revenue of about $400 or $450K.”
    — Siddharth Sinha [20:06]

• Profitability:

  • Profitable as of Q4 2025.
  • “Last quarter was our first profitable quarter so we are profitable now.”
    — Siddharth Sinha [20:52]

• Lowest Bank Balance:

  • "Tens of thousands" of dollars before turning profitable.
  • “Cash is more important than your mother.”
    — Siddharth Sinha [21:11]

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Market & Product Vision

• Where the Industry is Going:
  • The vision is to automate the digital marketing function for e-commerce brands—fully replacing digital agencies by programmatically generating the entire content strategy and asset set per-channel.
  • “We’ll be substituting digital marketing agencies. You wouldn’t need them anymore.”
    — Siddharth Sinha [21:59]

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Notable Quotes & Moments

• On Usage-Based Pricing:

  • “So essentially we are on a usage fee basis. Depending on how much content you're creating, that's how much we charge you... the platform customizes itself—but no cost to the platform itself, just the content you’re creating.”
    — Siddharth Sinha [05:27]

• On International Sales:

  • “You can have people based in India sell to large enterprise U.S. customers. You do need some face time…But [travel] is seasonal or periodic. We make sure we are in front of our main customers as often as we need to.”
    — Siddharth Sinha [18:59]

• On Profitability and Cash Management:

  • “I've run bootstrapped businesses before so I know how it goes…As they say, you know, cash is more important than your mother.”
    — Siddharth Sinha [21:11]

• On Company Vision:

  • “We’ll be substituting digital marketing agencies. You wouldn’t need them anymore. You’ll essentially be coming to us and we would create your entire content plan.”
    — Siddharth Sinha [21:59]

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Timestamps for Key Segments

• [01:08] — Dresma’s business model and customer use cases
• [02:09] — Example: How Puma localizes content via Dresma
• [02:54] — AI models and custom data layer explained
• [05:27] — Pricing model: usage, not seats or product
• [06:35] — Average contract value and credit system
• [10:56] — Channel partnerships and workflow with studios
• [12:11] — 50–55% of revenue from studio channel
• [13:05] — Free tools as lead-gen and SEO
• [15:46] — ABM tech stack & outbound approach
• [17:07] — Sales & marketing team structure
• [20:52] — First profitable quarter, how low the bank balance went
• [21:59] — Vision: replacing the digital agency with AI

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Summary Takeaway

Dresma demonstrates how a focused AI SaaS company can scale to $2M ARR by combining usage-based pricing, sticky data-driven features, diversified lead-gen, and lean global operations. Their journey provides practical insights for founders on structuring value-based pricing, orchestrating partnerships, bootstrapping sales with offshore teams, and building real value on top of commoditized AI infrastructure.

Siddharth’s vision is ambitious: to become the go-to engine for all e-commerce content—ultimately replacing traditional marketing agencies.

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Transcript

[A]

What does your largest customer pay you today?

[B]

Just about half a million dollars.

[A]

You're at 2 million right now here in December of 2025. And where were you exactly one year ago?

[B]

We were at about 1.3.

[A]

Everybody knows Puma the shoes. How does Puma use you guys?

[B]

Puma uses us to basically localize content for all the markets that they are in. To give you an example, we recently essentially helped them launch in Southeast Asia.

[A]

How low at any point in time did the bank balance get before you turn profitable?

[B]

Those are the tens of thousands of dollars.

[A]

So this year in 2025, they're finished here in December with $2 million of ARR28 paying customers, 31 team members. If I forced you to tell me on average what does a customer pay you per month or per year, what would that dollar range be? Hey folks, my guest today is Siddharth Sinit. He is building Dresma, an AI powered platform revolutionizing e commerce imagery. He's a Cornell engineer and Insead MBA alumnus as a serial entrepreneur leading his third venture as CEO and co founder of the business. All right Siddharth, you ready to take us to the top?

[B]

Great. Nice to meet you.

[A]

Nathan, good to meet you as well. Take us into the business. Right, so I'm going to pull up the website here, tell the audience what you guys do. How do you make money?

[B]

So we basically help any brand create all the content that they need to be successful online. Whether it be for marketplaces, for social media or for their own web store. So everything from videos to lifestyle imagery to the any content that goes on their PDP page. That's, that's what we do. We help the brands do this at scale with the studio quality.

[A]

So if I tried to pigeonhole you here, would you say this is more of a AI like Pinterest or more of a sort of SORA social network of AI images around merchandise from a specific brand or neither.

[B]

So this is essentially think of us as a marketing agency on steroids. So effectively we give you all the intelligence that the Regency gives you about your, about your brand, their, your environment and the LANDSC landscape as well as give you the workflows to be able to create content that makes you successful in that environment.

[A]

Okay, help educate me here. Let's just dive into a specific example. So let's pick one here on your website. Everybody knows Puma the shoes. How does Puma use you guys?

[B]

So Puma uses us to basically localize content for all the markets that they are in. So to give you an Example, we recently essentially helped them launched in Southeast Asia. So all the content that was designed for their European market was localized for the Southeast Asian market. We gave them all the sort of intelligence as to figure out what kind of context they should be showing their products on, what kind of models they should be using to showcase that product. And all of it was done using AI. They used AI models, AI locations, and essentially localized all the entire product portfolio for that, for that market.

[A]

And what sort of LLM stack are you sitting on top of? Or are you doing tool calling? And you just field the request to any of the different models.

[B]

So we essentially are primarily built on top of Gemini for all the content creation. We use a bunch of different video models depending on what kind of content you're creating. But for most of the imagery, we are using Gemini and we basically lay a data foundation below it so that essentially we are able to inform the model as to the best referencing, the best prompting that can be used to create content for that particular brand.

[A]

And Siddharth, a lot of folks are saying these AI tools are just wrappers. And the reason they say that is because so much of your revenue goes to paying for Gemini credits. What percent of your total revenue today goes towards paying for the credits?

[B]

So it's about 25 to 30%.

[A]

That's not bad.

[B]

So basically what the brand is also paying us for essentially are two things. One is the data layer itself. So we essentially have a lot of real time intelligence as to what kind of content brands should be creating. So that's one part of the value add that they bring on top of the LLM or the data creation layer.

[A]

So just to be clear, like lifestyle shots versus Catalog versus Marketplace versus Ad. That's what you mean by the kinds of content?

[B]

Yes, those are the kinds of content. But we essentially, if you look at the SOFA and the environment that that SOFA is sitting in, that information comes from our data layer. So essentially, given a type of brand and a type of product, you're able to essentially contextualize the product for the best appeal to the audience that the brand is actually pitching to.

[A]

And if I'm Puma, when I logged into dresma.com will I effectively see all of my products with basically all the related metadata and the variants on that metadata for certain geographies and product lines and human models?

[B]

Yeah. So basically, currently we are integrated with Amazon Seller Panel as well as a couple of different PIMs so that you can actually pull your data directly from those sources. And we essentially have built a profile of your brand and are able to track what kind of content is working for brands like yours in different markets. So then we use that intelligence to be able to be able to better advise the brand as to what kind of content they should be creating.

[A]

Let's shift to pricing. I either see people charging five bucks a month and they want a million customers, or they don't even show their pricing and they want 10 customers paying 5 million per year. You do both, you've got $5 over here and enterprise. Let's talk over here, what's the model?

[B]

So essentially we are on a usage fee basis. So depending on how much content you're creating, that's how much we charge you. Essentially the customization of the platform comes with usage. So as you're actually coming in, signing up and creating content, that's how we learn more about your brand and what kind of content works for you. And then the platform customizes by itself. So there's no cost to the usage of the platform itself, essentially just the content that you're creating. So basically it's the usage fee for that.

[A]

Yes or no, do you upsell based off number of seats from the Puma marketing team?

[B]

No. So essentially it's just the quantum of content that you create.

[A]

Okay, and last question here, true or false, you don't charge for product based upselling, just usage.

[B]

Yes, just usage.

[A]

Okay, very cool. So very focused on usage. You can see sort of how those credits work right here. Siddharth, I'm gonna force you into an average here, which I know engineers never love, so bear with me, okay? If I forced you to tell me on average, what does a customer pay you per month or per year, what would that dollar range be.

[B]

For a year? It'll be about 60k.

[A]

Okay, you answered that fairly quickly. What does that mean in terms of total credit consumption for that? 60k.

[B]

So 60k essentially on our platform is 60,000. 60,000 credits. It's the dollar credit. Pretty much one to one on that. Yeah, it's one to one. So only do you, when you get into very high quantum consumption, so upwards of say 200, $300,000, do we discount on the credit pricing?

[A]

Okay, okay, that makes a ton of sense. And give us the backstory now that we understand the pricing and the product. What year did you launch the business?

[B]

So the business launched in the summer of 2020. So we started off with essentially automating all the workflows that happen after photographs get shot in a studio. So essentially started off there. So we built a whole bunch of image processing algorithms that automated essentially what people would be doing using Photoshop. So that's where we started. So we have a very strong core expertise in image processing and understand what kind of images work for brands. And then over the last year and a half, two years, obviously we've sort of adopted all the new AI tools, essentially built that whole creative imagery layer on top of the image processing expertise that we have.

[A]

And how much did you spend to.

[B]

Launch the business from a tech investment? So I mean in terms of total capital raised so far, we raised $3 million and we are about a revenue of just under 2 million right now.

[A]

Well that's great. Okay, so you'll do, you're at 2 million right now here in December of 2025. And where were you exactly one year ago?

[B]

We were at about 1.3.

[A]

One point. Are you happy with that growth?

[B]

Not really. I would have had, I would have liked a little bit more than that. But what we've seen, I mean, I think with a lot of different generative AI companies is that there's been a lot of sort of POC work this year and not a lot of actual production. So that's changed in the last couple of months. We're actually seeing a lot of brands now adopting AI generated content for their bulk workflows for their actually their core business as well.

[A]

Guys, remember, I am not just a YouTuber, I'm investing in my third fund. We've deployed $250 million into 550 software companies so far. [e-mail] if you're interested in capital, I would love to cut you a check because I know you're investing in your education. You watch my show. So sign [e-mail] and when you get the onboarding email, I reply and I see all those, just reply and say Nathan, I found you through YouTube and I'll make sure to prioritize you. I would love to cut you a check. Check out founderpath.com and so you're doing 2 million of revenue right now. How many total customers are paying?

[B]

We have about 27 or 28 different customers.

[A]

Okay. And don't name them obviously, but what does your largest customer pay you today?

[B]

Just about half a million dollars.

[A]

Okay, that's, that's pretty impressive, right? To be at 2 million of revenue. You, you've now proven that there is a usage based upsell enterprise model where you can expand those accounts to half a million per year. That must get you excited.

[B]

Yeah, yeah. So we have two kinds of customers. Nathan. So we work directly with the brands, but we also do work with aggregators. So we have partnerships with studios where we co sell a solution to brands. So a lot of brands still need the product photography done. So they get the studio to actually do the product photography and then they use our AI algorithms to then transform those images into model imagery, lifestyle imagery videos, and all sorts of different workflows after that.

[A]

Give me the URL of an example studio you work with. That's one of your good partners.

[B]

So we are at, we work with ephoto in Italy. So ephoto works with most of the large luxury brands in Europe. So they do photography for them and they're using our.

[A]

Is this, is this it? This is their studio, something like this?

[B]

Yeah, yeah.

[A]

Is this their website?

[B]

Yes.

[A]

Okay, so now that my audience is seeing this here in their YouTube recording here, explain your go to market again on how you work with them.

[B]

So we work. So essentially if you look at somebody like for example, we did work with Champion recently, there's actually an ongoing project. So for Champion, essentially what Ecotour does is essentially does flatly shoots of all their products. They use our workflows then to take those flat lay shoots and convert them into model images, into videos, into lifestyle location imagery. So all of that is done using our AI workflows. The initial photography is done by ePhoto.

[A]

I see, I see, I see. It's almost like when we're building synthetic models to train, you know, train it, train to train the foundation models. Basically you are the data input. You are the, you know, they are, sorry, they are the raw input.

[B]

They are the raw.

[A]

You're then generating essentially if you look at static data on top.

[B]

Exactly. So if you look at the, if you look at what we have where AI can really help, I mean, you know, the product still is unique to the brand. It has very unique characteristics. So the AI can't really generate the original product itself. So that really needs still a good high quality image to get started with. And then you can take that image then adapt that into all sorts of different outcomes.

[A]

So let me ask you a question. How much of your revenue growth would you say has come from this partnering with studio strategy?

[B]

So currently about, I think 50 or 55% of our revenue comes from that, from that channel. We have studio partners in Western Europe, in Germany and France and Italy, as well as in a couple of them in the US as well. So we have, we are geographically diverse when it comes to partnerships that we've established in all our major markets.

[A]

So true or False. You've scaled to from a million to 2 million of revenue over the past 12 to 18 months. 50% of that growth has come from partnerships. Yeah.

[B]

Yeah.

[A]

Okay, cool. Any other growth channels you're using to scale? I notice in your footer you're investing in these tools and these can sometimes do really well for SEO and LM sort of programmatic SEO optimization. When we go look at your actual traffic hitting your website, that free tool strategy brings in about 4,300 clicks per month. Is that intentional?

[B]

Yes. So we do use so essentially for that. It's really a lead generation channel for us effectively that gets people to come in, try out the technology, make sure that you know, the, the core AI is there and then we work with the, with the brand to essentially to upscale, upsell and essentially get the platform adopted. Yep.

[A]

This is a huge. Guys, all you watching, you should copy what Siddhartha has done for your own industry or niche, Right. Which is make these free tools with very little friction in your footer. It's an SEO play, invest in the SEO all the way down the page so it pulls in free traffic. Right. And these are basically just small components, Siddhartha, of what your larger product does once they actually start paying. This works well for you. Your top performing One is your HD photo converter that's representing almost 50% that total traffic. A lot of people, Siddharth will say, yeah, Nathan, but this traffic doesn't convert. How would you respond to that? You're seeing the data.

[B]

So essentially what that does is it allows us to allow the customer to have a small foot in our door. Right. So it's just gets us, gets them onto router to our website, gets us aware, gets them aware of the solution that we are offering. Essentially. These are typically the way we sort of choose these, these keywords are designed typically sort of small wins that, that a marketing team or the studio team is looking for. So they may have a bunch of images that are of the wrong format and they need them changed and they need that, need them done quickly. So just this gives them a quick salute, quick win. So essentially come on to our platform and this social allows us to socialize the solution with them.

[A]

Are there any other growth channels you use to add over a million dollars of revenue over the past, you know, 12 to 24 months?

[B]

So we've essentially have done quite a bit of outbound work over the last year as well. So essentially a mix of email and LinkedIn outreaches. So we essentially have an orchestration platform that we built using some of the data enrichment tools out there to be able to essentially reach out to these, to, to our target audience in a very specific way.

[A]

So explain that tech stack to me with this graphic. Siddharth, this is a graphic of the 33 growth tactics CEOs. Tell me over and over you're talking about account based marketing here. You already educated us on how you're doing programmatic SEO with free tools. And you already educated us on how you're working with sort of these value added resellers or partners with the studios. You're also using the ABN. So teach us here. You've just broken $2 million of revenue. What does your ABM stack look like? What technologies and tools are you using here?

[B]

So essentially for the actual reach out and sequencing, we're using smart leads. We pair that with a sort of an add on, sort of orchestration tool that we sort of built built in house that helps us do sort of LinkedIn automation as well. For the data, we use Apollo and Clay as enrichment tools. So essentially Apollo as the data source and Clay as the enrichment tool.

[A]

So this site smart lead, right? Plus Apollo plus Clay, plus some custom stuff you built in house. That is your ABM strategy.

[B]

That's true.

[A]

Of the $1 million of new revenue you added in the past 12 months, how much has come from ABM?

[B]

That would be about, I would say 30 to 35%.

[A]

That's a big chunk. What's your team size today and how many are dedicated to sales and marketing and outreach?

[B]

So total employee count at the moment is 31. In terms of sales and marketing, we have five people right now across sales and marketing.

[A]

And for folks that are also around 2 million bucks of revenue, looking to scale, and they're watching this and they want to say, well, wait, Nathan, how did Siddharth structure those five jobs? What are they? Are they all SDRs? AES, what's the mix? Who carries a quota?

[B]

So essentially they're essentially. Currently there are two AES. We don't have SDRs at the moment. We have two AES and we have three people that are two and a half people looking at marketing right now.

[A]

Okay, so three marketing, two AES. When you hire your first AE and you're a seasoned entrepreneur, you've sold to other companies. Right? What, what quota do you give that AE when they start?

[B]

So we are looking at starting out with an AE in the first year. We would look at spring some anywhere between half a million to three quarters of a million dollars worth of revenue.

[A]

Okay, that's their quota target. And generally speaking, and don't reveal actual salaries and names, but generally speaking, for an ae, when you hire them at your stage, what's the base you're going to pay them?

[B]

So currently actually our AES are based in India. So we've actually had very sort of capital efficient that way. So our costs are actually very low. So we're essentially selling out of the. Almost the entire team sits out of India right now. All of our tech development happens out of India. So we actually have a very low cost base when it comes to that.

[A]

Those five on sales and marketing in India, which city? Chennai? Bangalore. Somewhere in Mumbai.

[B]

Here in. Near Delhi, in Gurgaon.

[A]

Okay, Delhi, Interesting. So are they, are they totally commission based or do they have any base salary at all?

[B]

No, they have base salary plus commission.

[A]

Okay, so base, is it fair to say it'd be under $20,000 per year? 20,000 USD?

[B]

The average of the two would be 20.

[A]

Okay, so guys, there you have it. There's another good data point for you. Interesting are those people say, Nathan, I can't have AES in India selling to big puma companies based in California. Is that true or false? Based off your experience, that's false.

[B]

You can have people based in India sell to large enterprise U.S. customers. You do need some FaceTime. So myself, my co founder and the salesperson at times will be traveling to the US and Europe. So those are seasonal or periodic trips that we make to make sure that we are in front of our main customers as often as we need to.

[A]

And Siddharth, So as we sort of wrap up here, I want to spend one or two minutes on fundraising questions and one or two minutes on where you see your product and your space going before we wrap. So on the fundraising, you raised 3 million. When was that round done? Was it all one round?

[B]

This was a seed round. That was the only external capital we raised. That was done at the end of 2021.

[A]

Okay, so 3 million seed. And was that a traditional safe?

[B]

That was a price round.

[A]

It was priced. Okay, look, I have to ask this.

[B]

What was the valuation at that time? We did a post money of 10 million.

[A]

Okay, how did you, how did you defend that? People will say, wait, it's pre revenue. There's not even one customer yet. How's he getting a 10 million valuation?

[B]

At that time? We did have revenue, so we were at about book revenue of about 4, 400 or 450k at the time.

[A]

Okay, so you use that traction to help defend the post money. Did you Rely on your past companies that you were at as well. You had some cachet there, some experience, some experience there.

[B]

Plus I mean both my co founders have very deep expertise in, in E commerce, especially content for E commerce they come in with. So basically they used to run studios for large e commerce enterprises in India as well as doing post production work for large studios in Europe. So they come with deep expertise in the, in the, in the vertical and.

[A]

Are you default alive today? In other words, are you profitable?

[B]

So we last quarter was our first profitable quarter so we are profitable now.

[A]

Congrats. That's exciting. How low at any point in time did the bank balance get before you turn profitable?

[B]

It was over tens of thousands of dollars.

[A]

How did that feel? Were you nervous?

[B]

It's very diverse but I mean I've run bootstrapped businesses before so I know how it goes so it's okay. So obviously you know, as they say, you know, cash is more important than your mother. So it's, it's important to keep, keep an eye on it. But you know, yeah, you have to stay a little bit conservative in those times but we were very confident of, of the business and the value we were bringing to our customers. So we didn't really have. I mean I wasn't that nervous.

[A]

Yeah, very good. Well, hey, take us home here. We're on dresma.com right now. The headline says your Visual AI Content Creation Engine. You know what products you're building for the next year. If I refresh this a year or two years from now, what's your headline going to say?

[B]

I mean essentially we'll be substituting digital marketing agencies. You wouldn't need digital marketing agencies anymore. You'll essentially be coming to us and we would essentially create your entire content plan whether it be for whichever content channel you need to reach your customers more.

[A]

Guys, there you have it from Siddhartha Senna launched back in 2020 did his 3 million pre seeded 10 million post with four $400,000 of revenue back in 2021. Fast forward to 2024 they broke $1.3 million of revenue. And this year in 2025 they're finished here in December with $2 million of ARR 28 paying customers. 3131 team members profitable in Q4 which we love. And get this, they've upsold against their usage based pricing model where their largest customer today is paying $500,000 per year. He's on to something. But it wasn't all easy. His lowest bank balance as he was building was in the quote, tens of thousands before he turned profitable. Now reinventing the visual AI content creation space specifically for e commerce brands that need to put the same shoe in six different languages with seven different models on a thousand different websites. Check it [e-mail] Siddharth, thanks for taking us to the top.

[B]

Thank you Nathan. Great talking to you.