AI in fashion: How Otrium uses AI for robotics and content creation

AI is rapidly conquering the fashion industry. While one company waits, another leads the way.

Outlet platform Otrium uses artificial intelligence both behind the scenes in the warehouse and at the forefront with generative AI content. Co-founder Milan Daniels explains how this makes the company faster, smarter, and more customer-focused. He also discusses the opportunities he sees for the future.

1. How do you view AI? What does Otrium use artificial intelligence for?

As a company, we are enthusiastic about the possibilities AI offers us. Developments are moving quickly. For us, it’s about testing, learning, and scaling what works.

We currently use AI in two ways. In our warehouse, we use robotics and automation, including Autostore: an automated pick-and-pack machine that uses AI to calculate the fastest routes for collecting orders. This saves costs and makes us faster for the customer.

Additionally, we use generative AI to provide images for products for which we do not receive product or model photography. This improves the presentation and increases conversion. We have been doing this for about four months. We introduced robotics and AI into our logistics process earlier this year, in April.

2. Tell us more. First: how did the automation and AI implementation in your warehouse come about?

The automation and AI implementation in our warehouse is technically very demanding and requires collaboration. We did this together with Bleckmann, our fulfilment partner; Kardex, the party that manages the machines; and Autostore itself. The four parties worked together to get the installation ready. There are decades of experience behind this – Kardex and Autostore also do this for many other companies.

For us, it was mainly a matter of getting on board at the right time. It was a significant investment and only possible because we have now reached a scale where it makes economic sense. That was a milestone for us.

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Otrium Credits: courtesy of Otrium

3. What impact has the AI-driven warehouse had on your operations? What has it delivered?

The difference is enormous. We have more capacity and need fewer staff, as the workforce has been reduced by 70 percent. It is also good that the warehouse staff have fewer repetitive tasks to do and, as I mentioned, we can serve customers faster.

Then there are the efficiency gains. We invest the money saved in better service or our marketing budget. This brings us closer to profitability.

Besides an order machine, we also have Genesis, a machine that packs boxes. A polybagging machine will also be added soon, which automatically puts products into a plastic bag.

At the same time, every system has its own learning curve. Working with people presents challenges, and the same is true for robots. Sometimes they stall and need to be restarted. That vulnerability and technical complexity is also part of it.

4. How do you use GenAI and what benefits has it brought?

Otrium works with 250 brands and receives five million items of stock annually. Sometimes model photos are missing or there are no rights for use on third-party platforms like ours. Because we mainly work with residual stock, the depth per SKU (unique item, ed.) is often small. This previously made it unprofitable to arrange expensive photography. However, a product does not sell well without model photos. Thanks to GenAI, we can offer this cost-effectively and thus improve the presentation.

We also now create in-house inspiration images and campaigns, for example, for targeted newsletters. Where traditional fashion brands work with seasons, we deal with constantly changing products. GenAI allows us to quickly build content around them. We could never have done that manually on this scale. Customer reactions to this have also been very positive.

5. What does AI demand from your employees? GenAI also brings its own challenges...

The challenge with GenAI is that new tools and services are constantly emerging. This creates a lot of movement and a certain amount of chaos. You might invest in one solution, and a month later a new version or an alternative comes out that works ten times better and is directly part of a larger suite, like with Google Gemini.

This requires enormous flexibility from our team. It means not committing to one solution, but constantly reassessing which tool best fits what we want to create. That is really different from before, where you chose one SaaS solution and worked with it for years.

6. Where do you see the biggest opportunities for AI in the future?

There are a few directions where we see a lot of potential. Sizing is a very important one. Not just for us, but for the entire fashion sector, of course. With the help of AI, we can move towards more uniformity in sizes. Think also about learning from returns and giving the customer better size advice.

A second is moving images. Model photography is now static, but if that becomes videos, it offers new functionalities where you can rotate or zoom in. That brings the online experience a few steps closer to that of physical shopping.

7. Do you have a tip for other fashion companies when it comes to AI?

I don’t like to tell others what to do, but I can share our experience. Otrium started with AI lookbooks early on, even though they didn’t look so convincing at the time. We knew it would get better quickly. My takeaway is: don’t wait for something to be perfect. Start with AI in good time and grow with its development. Those who join later risk falling behind and missing out on a competitive advantage.

Otrium recently launched a new segment: beauty. The company is also active again in the UK, with the market now being served directly from the flagship warehouse in Almelo.

Does your company use AI in design, logistics or inventory management? Let us know via tip@fashionunited.com and share your experiences with the editorial team.

Sources:
- Interview with Milan Daniels, co-founder of Otrium on September 22, 2025.
- AI tools for transcribing the interview and as a writing aid.

This article was translated to English using an AI tool.

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