Should You Build or Buy AR & AI Try-On Technology?

This blog is an extract from our white paper AI and AR Virtual Try-On: Reducing Returns Through a Strategic Approach to Implementation.

AR and AI Virtual Try-On is attracting growing amounts of investment from retailers with the promise to reduce product returns and boost conversion rates. Although the four independent studies we reviewed vary in terms of the current value of the market, from USD$15.18 billion (Mordor Intelligence 2025) to USD$3.8 billion (Worldwide Market Reports 2025), they all predict significant compound annual growth rates of between 28.5% (Market.US 2025) and 14.1% (Future Market Insights 2025) over the next 10-15 years.

However, these and other benefits can only be realised when the technology is used to solve a specific, quantifiable business problem, rather than in response to competitive pressure or innovation expectations. Once the business case for implementing AI and AR Virtual Try-On technology has been proved, the next big decision is whether to build the solution in house or buy it from a supplier.

This should be determined as early in the project planning stage as possible because the chosen route will directly influence the return generated on investment, so getting this right is vital to underline the business case – or undermine it.

So, where do you start? The first step is to carefully weigh up the pros and cons of each route, which vary between the two versions of the technology.

AR Virtual Try-On build/buy considerations

Using specialist platforms like Shopify AR, Zakeke and Threekit accelerates time to market because they are ready to roll immediately. However, they come with ongoing costs per interaction, underlining the need to research this financial burden well in advance so its impact on overall ROI can be accurately calculated. In contrast, custom builds provide more cost control, but they require specialist AR expertise. Without this in house, retailers will need to outsource, which can prove expensive. These costs need to be carefully gauged against using an external platform.

This version of virtual try-on technology uses a mobile device’s camera plus sensors to measure actual spaces. It then overlays 3D product models at an accurate scale in the physical environment using WebXR or native AR capabilities. Regardless of the platform retailers choose, this remains the biggest cost element in AR Virtual Try-On and must be acknowledged and factored in.

Faced with this rather complex picture, most successful projects we’ve seen have started with a third-party platform for core AR functionality, combined with bringing in a custom integration partner who has experience necessary for a smooth seamless implementation.

AI Virtual Try-On build/buy considerations:

Custom builds are rarely justified with AI Virtual Try-On unless the target product category is underserved by existing solutions. That’s because AI model development requires specialist expertise that most retailers are unlikely to have in house.

Furthermore, white-label solutions from the likes of Perfect Corp, ModiFace, Banuba and others are well developed for a wide range of specific categories. So, there’s likely to be one relevant to cover most products. These platforms also generally deliver fast time to market, lower upfront investment, continuous updates and lower risk.

They do, however, offer limited customisation. Plus, there’s one important factor to be aware of when setting budgets and calculating long-term ROI for AI Virtual Try-On solutions – computational costs scale with usage. This means the more successful adoption is, the more expensive the project becomes. This rising cost must be factored in when calculating long-term value.

The speed to market and limited risk make these platforms particularly appealing to retailers looking to act quickly to improve customer confidence and reduce return rates.

The real cost driver for both: Keeping up with innovation

With any successful AI and AR Virtual Try-On implementation, it’s important to recognise that costs are probably going to be ongoing. This means as a rule of thumb factoring in 20-30% annual costs for maintenance, updates and improvements.

Having quantified the ROI for such an initiative, you should feel confident that any and all ongoing expenses are within the budget created by your cost savings.

Read our white paper AI and AR Virtual Try-On: Reducing Returns Through a Strategic Approach to Implementation to find out how to develop a strategic framework to ensure AI and AR Virtual Try-On is applied appropriately from a problem-first perspective to solve measurable business challenges.