MCI x Rewe
It’s not always easy to keep fitness, nutrition, and day-to-day grocery shopping in sync. That's why this concept proposes an app that ties together personal health goals, meal planning, and supermarket inventories through a single platform.
Initially, users would enter basic personal information—such as age, height, weight, current fitness experience, dietary preferences, and their individual goals (for example: losing weight, gaining muscle or improving endurance). Based on this information, the app creates a custom training plan suited to the user's current level and desired outcomes. A beginner might receive straightforward workout routines to progressively build up strength, while more experienced users would see advanced exercises targeted to their existing abilities.
After establishing the personalized training plan, the app calculates exact nutritional requirements, clearly indicating how much protein, carbohydrates, fats, vitamins, and minerals the user needs daily. These nutritional guidelines are specifically aligned with the individual's training schedule and personal objectives, ensuring proper nutrition to support activity levels.
The final step involves integrating directly with local supermarket inventory systems. The app uses artificial intelligence to suggest recipes and snack ideas based entirely on ingredients currently available in-store. These suggestions are based on the user’s calculated nutritional needs, personal preferences, and budget, creating a more seamless and accessible way to eat in line with individual fitness goals.
Even though this concept could, in theory, be developed by any supermarket chain or fitness app provider, it seems particularly well-suited for a collaboration between REWE and the fitness app MCI. REWE already operates an app that lists its entire product range. While some localization of their inventory system would be necessary to adapt it for individual regions and product availability, the technical foundation for such integration is already in place. On the other side, MCI has already developed a fitness app that generates personalized training plans based on user-specific data like experience level, goals, and body metrics. Combining these two existing systems—REWE’s inventory infrastructure and MCI’s adaptive training logic—would significantly reduce the development workload. Instead of building everything from scratch, much of the functionality could be extended or connected, allowing the concept to focus on refining user experience, optimizing the AI-driven meal planning, and ensuring seamless communication between nutrition and training features.
This way, the concept becomes not just a new product but a logical evolution of existing technologies—bridging two systems that already handle key parts of the process. The result would be a fully integrated platform where personal fitness, nutritional planning, and local grocery shopping are no longer separate efforts but components of a single, coordinated experience.
AI Cooking
Cooking can be an enjoyable and rewarding experience, but it often feels intimidating or chaotic—especially when juggling recipes, timing, and unfamiliar techniques. This concept imagines an AI-driven voice assistant that transforms home cooking into an interactive, guided experience—more like a personal cooking class than following a static recipe.
At its core, the idea revolves around an AI voice chatbot that leads users step by step through the entire cooking process. From the moment preparation begins, the assistant offers clear, real-time instructions tailored to the selected recipe. The assistant is designed to be flexible and responsive. Users can ask for clarification, request substitutions if they’re missing an ingredient, or even slow down or speed up the process depending on how things are going in the kitchen. The dialogue is meant to feel like a back-and-forth conversation, where the AI acts more like a knowledgeable cooking partner than a rigid instructor. For example, if the user burns something or needs to pause to take a call, the assistant can adapt—offering troubleshooting tips or adjusting the flow of instructions without breaking the overall experience.
Each step is enriched with optional, AI-generated video tutorials that demonstrate techniques visually—ideal for users who are unfamiliar with certain methods or want a bit more confidence before moving forward. Integrated timers activate automatically when a step requires waiting, such as simmering a sauce or letting dough rest, so users don’t have to manually track time or risk forgetting. To make the experience more engaging and fun, users could choose from a range of voice personalities—like a calm, supportive tone for beginners, or a fiery Gordon Ramsay-style character for those who enjoy a bit of dramatic flair in the kitchen. There could even be a "couples mode," designed for two people cooking together, where instructions are split and coordinated so that both participants have clear roles and the process becomes a shared activity.For those interested in food culture and stories, a “Fun Fact” feature could be added to provide background on the heritage and history of the dish being cooked. While stirring a pot of Bolognese, the assistant might explain its origins in Emilia-Romagna, or share how certain ingredients became staples in regional cuisine. These little touches can turn a simple meal into a richer, more meaningful experience—connecting users not just to their food, but to the culture behind it.
What sets this concept apart is how it turns something that already exists in parts into a cohesive, immersive experience. AI tools like ChatGPT can already generate recipes and answer cooking-related questions, while other platforms offer possible voice interaction or video tutorials. But combining these capabilities into a single, dedicated app creates a much more immersive and usable environment. Instead of jumping between a browser, a smart speaker, and a recipe website, everything is unified in one place—with voice, video, timers, and guided support all working together in sync.
This app would essentially function as a virtual cooking teacher—one that’s flexible, conversational, and responsive. Whether someone is new to cooking or just needs help with more difficult recipes, the AI assistant would make cooking more approachable, less stressful, and ultimately more fun.
Mini-Mix
Choosing where to go out for the night often depends on one key question: what kind of music is actually going to be playing? While event flyers and club listings might show a lineup of DJs or artists, it’s often hard to get a real sense of the vibe without doing your own research—jumping between Spotify, SoundCloud, or Instagram to listen to individual tracks and figure out what each artist sounds like.
This concept aims to streamline that process by introducing an app that automatically creates a short, curated audio preview of the night’s music lineup. Instead of having to search every artist individually, the software pulls snippets of recent or representative tracks from streaming platforms and combines them into one seamless mini-mix. Think of it as an audio teaser that captures the overall sound and energy of the evening in under a minute.
The result is a quick, effortless way to understand the musical direction of an event. Whether it’s deep house, drum and bass or afrobeat, the preview gives users an instant sense of whether the night aligns with their taste.
In terms of application, this idea has strong benefits both for individual users and for businesses. For club-goers and music fans, it offers a personalized and convenient way to explore events based on sound, not just names or genres.
On the business side, clubs, promoters, and event organizers could use the app as a promotional tool. By generating automatic audio previews for their lineups, they can give potential guests a taste of what to expect—directly within their marketing materials, social media posts, or even embedded in ticketing platforms. This turns promotion into an active listening experience, helping attract the right audience and boost attendance. The app could also offer analytics for event organizers, showing which tracks or mixes generated the most engagement and allowing better insights into audience preferences over time.
Technologically, much of the foundation for this concept already exists. Platforms like Spotify and SoundCloud have APIs that allow access to artist profiles. These systems can be used to automatically pull representative snippets from each artist's recent releases or popular uploads. With some smart filtering and automation, this data can be processed and mixed into short previews that reflect the musical arc of an event lineup. Additionally, existing DJ software can be used to handle smooth transitions and consistent audio levels, making the mix feel polished and intentional.
This concept turns event discovery into a more intuitive and music-driven experience by letting people hear the vibe of a night before deciding where to go.