Streamlining content production for digital fashion brands - Michael Musandu, Founder of Lalaland

Lalaland has already proven to be successful with the biggest retailers in Europe like Zalando, Wehkamp, Otto and some of the biggest brands like PVH: Tommy Hilfiger and Calvin Klein.


Lalaland is a software that generates artificial full-body models for eCommerce brands, enabling them to show their collections on models that actually look like customers. The entire team consists of 14 people with many years of experience in computer science, artificial intelligence, fashion and business development. We caught up with Antonios to learn more about how this business idea came to be and what his vision is. Enjoy!

What's the story behind Lalaland?

I was born in Zimbabwe and raised in South Africa, where I first discovered my love for technology while developing low-level expert systems in school. Inspired to learn more, I moved to the Netherlands to study computer science at Vrije Universiteit in Amsterdam. There I met Ugnius Rimša, who eventually became my co-founder. During university, we developed several unique projects together, such as a simple Python script that automatically made reservations for high-demand and low-availability accommodations on the Amsterdam student campus. For years, we earned commissions with this and received a lot of praise from our fellow students. What we never managed to do, however, was develop something that could generate repeatable revenue. I knew I wanted to work with this guy who was able to scrape virtually anything off the Internet. We just did not know what exactly it was at that point. Next, I decided to jump on the 'hype train' and completed a graduate program in Artificial Intelligence at Utrecht College.

There I discovered generative adversarial networks, neural networks that capture variations in data sets within data sets. I was curious about the possibilities of commercializing such networks, so I joined Utrecht Inc, which helps young founders turn projects into businesses. The strange thing was that I had already found a solution, but was looking for a problem that could be solved with their technology. This is where the third partner in crime comes in: Harold Smeeman. Michael and Harold got to know each other during the incubation program and realized that they both felt severely underrepresented in online shopping as black and plus-size consumers. How do these clothes actually look and fit on people like them? That's when Lalaland was born, to diversify the Internet and solve the problem of people feeling underrepresented online.

Tell us about your previous professional experience. How did it impact the founding and business development of Lalaland?

We are uniquely qualified to implement this business model because we bring together technical and commercial experience in eCommerce and advanced machine learning. We have proven that we are able to get projects across the finish line with solid planning, a get things done mentality and tenacious execution.

The two technical co-founders come from computer science and artificial intelligence backgrounds and have experience with neural networks and machine learning models. Both co-founders have been able to attract highly talented Cumlaude-status graduates who are in the top 2% of engineers at their respective graduate schools. Our commercial co-founder has already successfully founded and exited his previous startup.


  • Ugnius Rimsa worked for fashion startup FashionTrade (funded by Zalando and Bestseller).
  • Harold Smeeman founded his first startup (WDS - Wireless Data Systems) and successfully exited it.
  • Michael Musandu comes from computer science and artificial intelligence background and has already gained entrepreneurial experience.

What problem does Lalaland solve and how would you say it eases your customers' pain?

Currently, brands have to do 2-8 photoshoots every year to release a new collection. Photoshoots are expensive because they require human models, photographers, makeup artists, hairstylists, venues, etc. That is, the biggest costs are

  • Missed opportunities for customer acquisition (because customers can not see the clothes on someone who looks like them).
  • High return rates because most returns are due to poor appearance and fit. The way the clothes fit and look on most models is usually not representative of how they fit the end consumer.
  • Environmental impact: 2.3 billion kilograms of waste are generated annually from discarded fashion returns that end up in landfills or incinerators.
  • Speed to market: When fashion brands are unable to keep up with content production during the photo process, this very often results in brands posting product images online without models, as seen in this example here.

Lalaland's platform effortlessly generates models of different ethnicities, ages, and sizes with more than 5 pose variations and offers a high degree of flexibility, allowing brands to customize models to match their customers' hairstyles and body shapes: Hourglass, Apple, Triangle, Pear and Rectangle.

Next, a highly efficient workflow combines product shots of mannequins with AI-generated model images. The result is realistic, publication-ready, large-scale model shots created in a fraction of the time it takes a traditional model photo to complete the following "self-service" steps:

  • Configure models - Choose skin color, body size, body shape, identity, hairstyle, and poses from hundreds of options.
  • Upload SKUs from product images entered either from digitally designed garments or from a mannequin product photo.
  • Dress models. Based on the selected models, model poses and the uploaded garments (SKUs), customers can compose different SKUs to create different looks/styles on model images.
  • Receive images - Once a fashion brand receives the images, they have the option to approve or reject them (and provide feedback) on the platform. The entire retail automation process is complete! And it can be added to the web store immediately.

The benefits:

  • Automation of the traditional process.

Currently, brands need more than 20 steps from planning a photoshoot to the final release of a collection online - not to mention reshoots. Lalaland has reduced this to 4 steps.

  • Faster time to market.

This process typically took 3 to 4 weeks. Lalaland has shortened this process to a few minutes.

  • Many more models.

Due to the cost of hiring models and the availability of models, fashion brands typically cast 2 to 4 models per collection. With Lalaland, brands can instantly select multiple models from a database of hundreds of synthetic models.

  • One-Stop-Store.

From dealing with model agencies to hiring locations, hairstylists, makeup artists, models, photographers and post-production companies. Lalaland drastically reduces third party involvement to a single product offering.

Is there a similar solution on the market?

Lalaland's competitive landscape: Physical, traditional photography - Non-conversion images.

A. Limited number of different, real models

B. Slow processes limited by the physical world.

C. The separation between what you see and what you are

D. Complicated & expensive legal procedures

Software-based image processing:, Zeekit (bought out by Walmart), ModelMe, Looklet,

How Lalaland is beating the competition:

  • Consumer Data/Insights.

We know what kind of models online shoppers want. Our on-model imagery is integrated via an API that allows our model recommendation engine to learn "on-the-fly" and dynamically adjust different models for different consumer segments on each product item.

  • Leading the way - first mover

The fashion industry is extremely demanding and obsessed with perfection, pixel by pixel. Therefore, a crude go-to-market strategy simply does not work.

This is now a competitive advantage, because new players in the industry have to invest a lot of time and money in product development and the industry sales process before they can catch up. In the last 1.5 years, we have focused a lot on product development, and that is now an advantage (and has been validated by the market in the meantime through all the indirect sales and POCs/paid betas we have done).

  • Proprietary Data.

Lalaland has proprietary data sets that are used prior to data pre-processing and machine learning algorithm training.

  • Constant research and development in the creation of models.

Lalaland is at the forefront of technology that allows us to create extremely high-quality models. With several PhD engineers in-house, we are constantly re-implementing everything found in the scientific literature. Research and development will always be at the heart of the product.

  • Full body modeling with true diversity.

Most returns are caused by poor appearance and fit; full body modeling (as opposed to synthetic faces) uniquely solves this problem. Consideration of all character traits, i.e. different hairstyles per ethnicity and different features per ethnicity (blacks have bigger lips and South Americans have wider hips).

What companies could use your solution? What are your target audiences and what has been the initial response?

  • Based on a deep understanding of the market, our current target customer is:
  • Fashion brands in the apparel industry
  • Companies with a digital turnover of at least €5 million+.
  • Brands with at least four collections per year in the mid to lower fashion segment
  • Company based in West Europe + North America (East Coast)
  • C-level (leadership) CEO, CIO, managing director, commercial director, marketing director, creative director & Head of Roles (Management) Head of Omnichannel operations, Head of eCommerce, Head of Content Production, Head of Digital Strategy, eCommerce Manager, Marketing Manager, Brand Manager, Innovation Manager.

How big is the opportunity they represent?

The global fashion industry is $3 trillion, which is 2% of global GDP. Lalaland looks at the growing 407.6 billion fashion e-commerce market, where 7.5% of annual sales are spent on photography and models for web shop product detail pages.

  • Total market available (TAM) : €19.7 billion/year (+€ Advertising market +€ Metaverse +++)
  • Served available market (SAM): €6.8 billion/year
  • Market share (SOM) : €67.8 million/year

What is the traction you have today?

  • Retailer - Highlights include: Zalando, Wehkamp and Otto.
  • Brands - Highlights include: Tommy Hilfiger, Calvin Klien, PVH , AdoreMe

What's happening in the industry you are in? What are the key trends?

  • 01 The Metaverse.

Synthetic models that exist only in the digital world will allow brands and consumers to control visuals in the metaverse.

  • 02 Digital Fashion.

Digital fashion houses like The Fabricant are leading the way and digital fashion is on the rise. Several brands are shifting to both apparel design (clo3d, grosso moda, browzwear) and product presentation in web stores, which is digital (stitch 3d, hatch), while model photography is still physical. The willingness of fashion brands to use end-to-end solutions (on-demand manufacturing) is high. This would in turn lead to a reduction in overproduction and fully digital solutions.

  • 03 Virtual Influencers / Avatars.

How people want their avatars to look and wear them, offering insights for fashion brands targeting a customer who spends time and money in digital worlds. With virtual influencers like Shudu and Lil Miquela, Lalaland can play an important role in creating virtual influencers for fashion brands.

  • 04 NFTs in Fashion.

Fashion has increasingly embraced NFTs, or non-fungible tokens, just as gaming and digital fashion have come to the fore. Garments are now frequently traded digitally. There is a market opportunity to have these digitally traded garments worn by avatars/synthetic models.

  • 05 Diversity and inclusivity in fashion

Women in particular feel unrepresented by existing fashion models.There is an urgent need in the fashion industry for broader representation on its websites, particularly of plus-size, multiracial, LGBTQI+, diverse gender identity, people with disabilities, and other underrepresented groups in the world.

  • 06 BLM (Black Lives Matter Movements)

BLM (black-lives-matter) and other movements dominate our thoughts and news cycles. Whether PR or real, this is forcing brands to show that they care about certain social issues, such as more diverse representation in their web stores.

  • 08 Body Positivity Movements.

The body positivity movement has become one of the biggest pushes against the lack of diversity and positive self-images in the fashion industry. In short, body positivity is the idea that all people should have a positive body image. The body positivity movement challenges the way society promotes unrealistic beauty standards. The movement advocates for the representation of all body types, sizes, physical abilities, races, and genders.

  • 09 Sustainable Fashion.

There is a growing awareness of fashion's impact on the environment. Sustainable fashion (also known as eco-fashion) is a movement and process that promotes change in fashion products and the fashion system toward greater environmental integrity and social justice. Using a solution like Lalaland's that has a sustainable impact is very important for brands to show their customers that they are committed to sustainable fashion.

  • 10 Covid - limiting physical photo shoots.

The Coronavirus also presents the fashion industry with an opportunity to completely reshape the industry's value chain, particularly in the area of fashion photography. Fashion brands have been scrambling to find alternative solutions to the lack of availability and limitations of on-location photo shoots with models. Fortunately, a solution like Lalaland's provides a remedy.

  • 11 Remote Work and the Globalisation of eCommerce.

Covid has accelerated remote work, and with Lalaland, people can now start a fashion brand in one country and sell directly in another, and do so completely seamlessly.

Imagine, a local brand in Lima can now sell high-quality garments made from Peruvian wool to international markets, using models that appeal to their target audience, without having to fly anywhere or schedule a photoshoot. Lalaland is enabling fashion brands around the world to serve customers in new markets, which otherwise would have been both difficult and expensive.

Where do you see Lalaland in 3-5 years?

Once Lalaland is ready, it will support fashion e-commerce brands in all segments such as women's, men's, children's and unisex fashion. A strong knowledge base, our on-model imagery integrated via an API that allows our model recommendation engine to learn "on-the-fly" and dynamically adapt different models to different consumer segments for each product item, will give us the ability to collect extremely valuable data on how to visualize consumers.

Lalaland will expand into different markets such as advertising and marketing. Being a technology-based company will always be in our DNA. We will challenge the status quo with breakthrough technology and evolve our modelling from images to videos to potentially compete with Hollywood.

What makes Lalaland so special? Why should investors choose you?

We are uniquely qualified to execute on this business model as we combine technical and commercial experience in e-commerce and cutting-edge generative AI. Lalaland has already proven to be successful with the biggest retailers in Europe like Zalando, Wehkamp, Otto and some of the biggest brands like PVH: Tommy Hilfiger and Calvin Klein. Backed by some strong strategic investors such as Google and Bart De Wilde (former CEO of Nike), Lalaland aims to make the Internet a more diverse place that brings significant benefits. Not only in financial terms, but also in terms of all three aspects of the Triple Bottom Line (TBL): people, planet, and profit.


Lalaland is running an exclusively private round, accessible to selected investors. To gain access, become a member of the SeedBlink Club.

By Bianca Iulia Simion

PublishedApril 18, 2022

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