Doopic AI is here
Traditional photo studios and photoshoots are becoming a thing of the past — welcome to a new digital era where high-quality visuals are generated faster, smarter, and more efficiently than ever before.
Doopic AI
Die Mission
Our goal is to offer clients a fully integrated process that transforms a single product into a complete spectrum of visual content.
From simple design samples or basic product photos — whether on mannequins or flat-lay — entire visual worlds can now be created. Doopic delivers not only virtual models, but also dynamic content such as product videos and on-location footage.
These visual experiences are enriched by the representation of diverse ethnicities, body types, and age groups, allowing eCommerce retailers to showcase their products in ways never before possible.
By simultaneously training custom-tailored AI models, we automate and scale the entire workflow. This enables us to reimagine product detail pages (PDPs) in collaboration with our clients — turning them into immersive brand experiences.
We are already partnering with some of Europe's largest retail companies — and the list is growing.
Virtual Try-On Model (VTON)
Goals:
Our clients face constant pressure to deliver visual content faster, more cost-effectively, and at the highest quality. To gain a competitive edge, all three factors must be improved beyond the limits of traditional production—while preserving full creative freedom and unlocking new design possibilities.
Approach:
Virtual Try-On uses a combination of AI-powered technologies to digitally display apparel and accessories on models or avatars. It replaces traditional model shoots across various contexts, accelerates production, and has the potential to significantly enhance the online shopping experience. Key advantages also include recontextualization, sustainability, and the flexible combination of products.
Challenges:
Virtual Try-On enables the digital visualization of apparel and accessories on models or avatars using a combination of AI-driven technologies. It replaces traditional model shoots across various contexts, accelerates production, and has the potential to sustainably enhance the online shopping experience. Key factors include recontextualization, sustainability, and the flexible combination of products.
Status:
We are currently in the active live testing phase with clients to further develop our VTON model technology in real-world settings. This live environment allows us to incorporate client feedback directly into our process and benefit from A/B testing to continuously refine and optimize our solutions.
Models and Products On-Location
Goals:
Visual content from on-location shoots is often limited due to the significant time and financial investment required. However, demand for this type of lifestyle-driven imagery has grown considerably—driven by channels like social media and the increasing pace of seasonal transitions.
Approach:
AI-based on-location simulations provide an additional layer of creative flexibility by working with existing image assets. They enable the generation of endless setting variations and deliver high-quality, diverse perspectives.
Challenges:
Supplementary visuals often need to meet campaign-specific requirements that go beyond standard product image guidelines. Integrating these creative specifications into standardized workflows remains one of the key challenges in this area.
Status:
We are conducting promising tests with our partners and are already able to offer our clients personalized previews.
Want to discover how our AI is transforming content creation?
We’re happy to share our expertise and vision for the future. Schedule a meeting with us!
Doopic AI
The value of AI lies in the process.
AI holds great potential in product image editing and generation. Many challenges that brands face today already have viable AI-based solutions. Costly production steps can be replaced, more variety introduced, individual style characteristics learned, and repetitive tasks fully automated.
As a SAAS and outsourcing partner, we go beyond one-off tasks. AI’s true value emerges when it’s seamlessly embedded into standardized, on-demand workflows. Only when we offer a complete lifecycle for AI-processed content can this potential be fully realized.
Image to Video
Goals:
The growing use of video as a complementary form of product presentation reflects not only evolving consumer expectations but also directly influences our clients’ content demands. Increased effort, higher production costs, and missed opportunities are key challenges we’re addressing. Product videos are proven to drive sales for many reasons — which is why we’re developing this solution for our clients.
Approach:
Image-to-Video brings together key benefits of the digital content pipeline in a single solution. It integrates smoothly into production workflows and creates color-consistent, dynamic videos from both real model photos and VTON outputs — effectively extending the use of generative content.
Challenges:
Given the frequency of unstable results, the complexity of prompt management, and the difficulty in accurately reproducing material textures, we’ve opted for a standardized foundation with minimal motion logic. We're advancing the technology gradually and iteratively.
Status:
We’re currently conducting promising tests with our partners and can already provide tailored previews to our clients.
Virtual Model Database
Goals:
New processes and products are more easily adopted when they follow familiar patterns. Instead of time-consuming back-and-forth when selecting AI-generated models, our clients want reliable standards they can quickly align on internally.
Approach:
A virtual model database enables familiar decision-making patterns, allowing pre-trained models to be deployed more quickly and integrated into standardized workflows. It also significantly improves the performance of product presentation and brings us closer to what customers are asking for. The principle: click and dress.
Challenges:
The goal is to reflect natural diversity without relying on stereotypical or conventional industry standards. We aim for the highest possible consistency across all relevant variations — including age groups, gender, ethnicities, skin tones, hair colors, hairstyles, body types, and more. Developing such a broadly high-performing model still requires significant effort at this stage.
Status:
As part of our pilot projects, we’re already working with our model database. The next step is making it permanently available within standardized workflows.
Data Enrichment
Goals:
Color variants, styles, attribute breakdowns, models, and styling items — the possibilities for micro-analysis and automated data processing are vast. However, they often fall short due to inconsistent or incomplete underlying data structures.
Approach:
AI-powered image analysis tools can fill gaps in incomplete datasets by adding the specific data points clients need.
Challenges:
The coordination of various tools with individual data sets is still too imprecise for some data points to be used reliably without manual correction.
Status:
Testing of various tools and evaluation of results within the regular workflow.
Want to discover how our AI is transforming content creation?
We’re happy to share our expertise and vision for the future. Schedule a meeting with us!
KI Bildkontrolle
Goals:
Despite system-supported quality control processes, more than 30% of the time our team spends on an image is still dedicated to manual review. This remains a significant cost and time factor.
Approach:
A custom-trained, AI-powered quality control tool can identify optimization opportunities more quickly and in ways that align better with the client’s specific standards.
Challenges:
The key added value lies in the AI’s ability to learn from client feedback. Generating meaningful results in this area requires extensive testing and refinement.
Status:
Internal testing in the area of advanced image analysis.