From General AI to Useful Products: How Deniz Güney Is Building for the Next Phase of Consumer AI

Access to increasingly capable AI tools has become more widely available. Anyone can open a chatbot or an image generator and, with enough patience, produce something impressive. The more complicated question is how to turn raw model capabilities into a workflow that feels intuitive to an ordinary user from the outset.

That question sits at the centre of how Deniz Güney builds. Güney is the founder of Rocket Digital, an app studio that has spent several years shipping consumer AI products for a global audience across image generation, video creation and computer vision. He treats the portfolio as a laboratory: launch focused products, watch how mainstream users behave, and double down where the AI removes friction people genuinely feel.

“General-purpose models are remarkable, but most consumers don’t want a model. They want an outcome,” Güney says. “Nobody wants to engineer prompts or compare model versions. They want the sofa question answered: will this look good in my living room?”

DecorAI: building an AI interior design app around an outcome

One example of that approach in Güney’s portfolio is DecorAI, an AI interior design app for iOS, Android and the web that allows users to upload a photo of a room and generate possible redesign concepts.

The official DecorAI app, developed by Rocket Digital, is designed around a relatively simple workflow. Photograph a bedroom, living room or kitchen, choose a direction, and compare concepts of the space in different styles. There is no prompt box and no technical vocabulary. The product translates plain choices, such as room type, style, and desired change, into the generation work behind the scenes.

Interior design may be a natural fit for this kind of specialised interface. The task is visual, so the output explains itself, and personal, so people care about the result. Traditional options, such as hiring a designer or learning professional visualisation software, may not be practical for every household. Many people instead rely on paint charts, measurements and their own judgment when planning a room.

Where vertical AI creates value

Güney’s argument for vertical products is an argument about abstraction. A general tool exposes capability and asks the user to supply the workflow. A vertical product embeds the workflow and hides the capability. When someone uses DecorAI to test furniture in a photo of their own flat, the value is not access to a model. The value is that the product already knows what “test furniture in my flat” means.

That framing changes what the product must be good at. “For most consumer AI products, defensibility doesn’t have to come from owning the model,” Güney argues. “It can come from understanding one job better than anyone else — which choices users want to make, which they want handled for them, and what they do with the result afterwards.” Those answers only come from shipping and iterating, which is why he regards his portfolio approach less as diversification and more as compounding user understanding.

Beyond AI room design: how DecorAI can support real decisions

DecorAI’s potential uses suggest that its role may extend beyond applying different styles to a room. Users can redesign existing rooms across more than 60 styles, but they also visualise specific furniture in their own space before buying, furnish empty rooms, and strip existing furniture out of a photo to start from a blank slate. Virtual staging, long a paid service in property marketing, becomes something anyone selling or letting a property can attempt from a phone. The app can also analyse a room and suggest improvements, and the same photo-to-concept workflow extends to exteriors and gardens, edging the product from AI room design towards broader AI home design.

What connects these use cases is that each may inform a financial decision, whether a renovation, purchase or property listing. AI-powered home visualisation can offer additional context before people commit to changes that may be costly or difficult to reverse. Seeing a possible version of a space before committing may help people evaluate their options and communicate their preferences more clearly to partners, landlords or contractors.

DecorAI, the AI interior design app published by Rocket Digital, is available on iOS, Android and the web in more than 20 languages, including Spanish, Japanese, Korean, French and German. Distribution reflects the same philosophy: anyone can generate three AI designs a day free of charge in the official DecorAI app, no account required, before deciding whether to pay.”

The founder lesson

For entrepreneurs, the interesting question is where DecorAI’s defensibility comes from. It does not depend on owning a foundation model; Güney’s company does not train frontier models and does not need to. It comes from the layer above: product design that removes prompting entirely, a workflow tuned to one task, distribution across iOS, Android and the web, and the accumulated understanding of how non-technical users behave when AI meets a household decision.

The lesson repeats across the current cycle: access to increasingly capable foundation models is becoming widely available. What remains less common is the work of shaping that capability into a tool with a clear purpose. Founders who take this approach may have opportunities to develop consumer businesses even as much of the industry remains focused on advancing the underlying models.

It also changes how consumer AI ideas get judged: whether AI can technically do something is becoming a weaker filter as model capabilities expand. The harder test is whether a product makes the task feel effortless for someone who will never read a changelog, and whether that task matters enough for them to come back.

Güney’s bet is that the next wave of consumer AI winners will look less like impressive technology and more like ordinary tools. “Our best users never think about AI at all,” he says. “They think about the wall colour, the sofa and the move-in date.” When the technology becomes that invisible, it has stopped being a novelty and started being a product, and that, more than any model announcement, is what the next phase of consumer AI will most likely reward.