How Botika is transforming brand content creation with AI-powered fashion photography

Doubling your customer base is a common goal that most fashion startups share. But doubling your customer base within the span of a month? That's a different story, one that Botika AI, a generative AI fashion company specializing in the creation of content and product photos using AI models, found itself in last December. A perhaps enviable, but certainly challenging and stressful position to be in, the company struggled with the influx of demand.

"It felt like everybody was running around in circles and everything was kind of breaking while we were working to fix it," recalls Eran Dagan, co-founder and CEO of the Tel Aviv-based company, during a Zoom interview with FashionUnited. "We didn't have a large enough team at the time to support all of our customers, so we had to scale our internal and retouching teams, which took us some time." He admits that the company did have to let some of its customers down, but those are just the growing pains of a tech startup. The company has since invested heavily in scalable infrastructure and team expansion to better handle future growth surges.

A steep learning curve for Botika, which was founded in 2018, Dagan kept looking at the bright side. "I kept telling our investors, 'Look, it's good problems, but there are still problems.'" The type of rapid growth story companies dream of, product innovation and expansion, are just two of the core components of Botika. Officially launching its online platform in January 2024, Botika currently serves over 3,000 fashion brands around the world and has secured $18 million in funding. Multiplying its revenue by nine and its customer base 11 times in the past year alone, we spoke with Dagan to learn more about how Botika is changing the fashion photography landscape.

The co-founders went from young entrepreneurs to AI fashion pioneers.

Dagan's journey to AI-powered fashion began long before generative AI entered the mainstream conversation. A self-taught programmer who started coding at 14, he founded his first business at 16, a B2B marketplace for used cars, leasing, and insurance. After selling that venture at 18, he served in the Israeli military while simultaneously building a TV show discovery app that scaled to millions of users from his dorm room. Entrepreneurship was in his blood.

Driven by his passion for creating the perfect product for his customers, it was during military service that Dagan met his co-founder, Yarin Didi Meir, whose background reads like a resume of a tech genius in the making. Meir completed his bachelor's degree in computer science at 15 and was recruited at 16 to work with a university AI lab team of PhDs and master inventors. What made this collaboration particularly foresighted was the team's focus: they were researching foundation models and generative AI 13 years ago, long before these technologies had become mainstream.

"His kind of bread and butter are large-scale AI models. He knows how they work and is building them," Dagan explains of his co-founder's expertise. The pair's friendship led to a pivotal decision in 2018 when they purchased their own GPU and began training a generative AI model from scratch. However, the founders didn't have their sights set on breaking into the fashion industry; rather, it was something that came along more intuitively. The AI technology the founders were developing excelled at simulating physics and understanding complex visual relationships, but its application remained an open question. "We knew that we didn't want to generate purely entertainment content. We wanted to create usable, useful content," says Dagan.

How AI is changing the fashion photography landscape

Initially, the duo considered developing virtual try-on technology to assist brands in offering their customers the ability to see how garments would look on them digitally. However, direct conversations with potential customers revealed a different path - and a gap in the market. "When we spoke to brands, we said, 'Hey, you know, we can do this. We can do that.' They told us, 'Well, you know it's good, but what we really need is the photo shoot part done like yesterday.'" Offering fashion photography using AI-generated models helps streamline workflows while reducing costs, which is a key selling point for Botika. Even before Dagan and Meir had a finished product, brands were expressing immediate interest in the technology. "We got this amazing feedback that everybody just wanted to use it instantly, and we didn't even have a product back then. It was just the technology," notes Dagan.

While cost savings might seem like the obvious selling point for AI-generated fashion photography, Botika's customers also benefit from a more nuanced value proposition. The platform's ability to generate diverse body types, facial features, and representations has addressed a challenge many brands didn't even realize they had - the need for diversity in the industry. Dagan reveals that during a recent trip to New York, he spoke with a hundred-million-dollar brand that articulated this challenge perfectly. "They told me, 'Look, we just pretty much ran out of models that aren't 'perfect, aka the type of models that align with the values we want to show in our visuals, ' and now it's extremely hard for that brand to find new models," he explains.

The brand in question specifically sought variety in body shapes, face structures, and features to better represent their diverse customer base. "Most brands are actually looking for that diversity, and that is much easier to achieve with AI than trying to find people who aren't usually going to model with certain characteristics," points out Dagan. Challenging the notion that AI-generated models promote unrealistic beauty standards, Botika aids brands in showcasing diversity. As none of the company's models are based on real people, with every model made from scratch using Botika's proprietary AI system, Botika is able to provide a wide range of models that traditional modeling agencies might struggle to provide consistently.

Botika AI fashion photography focuses on diversity and realism, while keeping the human touch

Despite offering a product that centers on AI-generated humans, maintaining a human touchpoint and expertise within its workflow is an important part of Botika's business. For example, the dedicated retouching team provides a safety net that customers value, and the customer service team means clients "always have a human" that they can talk to if they need to. A hybrid approach, it is another example of how companies can leverage artificial intelligence for efficiency and scale while preserving human expertise for nuance, quality control, and customer relationships.

Outside of Botika's accelerated growth over the last year, customer success stories have validated the company's unique product offering and approach. A case study by Botika with its customer, Juan & Me, an Australian brand, highlighted significant conversion rate and time-to-market improvements after implementing AI-generated photography. At the same time, it also opened up discussions within Juan & Me's local creative community about how AI can augment rather than replace human creativity.

The results have been equally compelling for larger clients as well. A major US-based fast fashion retailer (whose name cannot be disclosed for legal reasons) reported that Botika's AI-generated models rank in their top three performers immediately after launch, demonstrating that artificial models can compete effectively with traditional photography in driving customer engagement and sales. However, in spite of these success stories, it's evident that the fashion industry's relationship with AI remains complex.

Botika's unique hybrid approach

Ongoing concerns, ranging from job displacement to authenticity questions, remain. Dagan acknowledges these worries while further positioning Botika as part of a hybrid approach rather than a wholesale replacement for human creativity. "What we see brands doing with Botika is taking a hybrid approach, where they can use Botika for a lot of their photography but still have people working on the socials, their influencers," he explains. "Community really matters, which is where the human aspect is extremely valuable."

So far, this has been reflected in Botika's adoption rate as well. While many brands in the United States and the United Kingdom have been quick to test out the product, European brands, in particular, have shown more cautious adoption patterns. A large group of German brands using Botika expressed concerns about customer reception, leading to a gradual implementation strategy, notes Dagan. "You don't have to replace everything at once," he advises. "You can always dip your toes, see if it works for you."

A more measured approach that many brands seem to be testing, it also aligns with the company's broader philosophy moving forward. The company's current roadmap focuses on offering personalized content that helps customers connect with products without literal representation. The goal is to show "something that's realistic, that looks like them, that resembles how they perceive their bodies and features" rather than pursuing the "extremely perfect AI models" that might seem like an obvious commercial target.

Gradual AI adoption & the future of fashion photography

An updated version of Botika's AI, developed over the past six months, is set to launch on October 1st, 2025, to further this mission. The enhanced product offering is said to offer brands more realism and an expanded variety of body shapes and facial features, continuing Botika's commitment to real diversity in fashion imagery.

The overall focus on steady refinement, with a hybrid approach over revolutionary jumps, reflects what is happening in the fashion and tech landscapes, noted Dagan. The broader industry trajectory, according to Dagan, is moving toward more measured AI adoption. "We're going to see a bit more gradual adoption in the next couple of years and less of that all-or-nothing approach that we've seen in 2023 and 2024," he predicts, which reflects the change in how brands understand AI's strengths and limitations.