15-Second Generation, Editable, Interactive: This AI Home Game Wants to Make Space a 'New Content' for Everyone to Create | Interview with SenBOX

This article is reproduced with permission from "Game Art".

​In recent years, AI has already demonstrated powerful content generation capabilities in text and video domains. Many small teams and indie game developers have widely applied AI to NPC dialogue, art generation, and other areas. However, in the generation of interactive 3D spaces, the industry is still relatively early—modeling, layout, materials, lighting, and rendering still rely on professional software and trained creators.

If AI could generate game scenes, spaces, and even go a step further to build an interactive virtual world where the game world is no longer entirely pre-built by developers but instead allows players to participate through AI, co-creating, sharing, and enriching virtual spaces—this sounds a bit like the "metaverse" from a few years ago, but the underlying technological implementation is already completely different.

Recently, SenBOX won the Best AI Game Nomination Award and the "Most Commercial Value Award" at the second "Shu Long Cup" Global AI Innovation Awards hosted by Century Huatong. The product's developer, Shengjing Technology, chose to start from "home": users input a sentence, a reference image, or even just a vague inspiration, and the system can generate a 3D home that can be further edited.

Since entering the public eye last year, SenBOX has accumulated nearly 2 million fans across the entire network, with a total exposure exceeding 300 million. Reservations on TapTap have reached 240,000, and about 4,000 users participated in the beta test, generating 1.2 million room states. Currently, the product is about to open a new round of testing and is expected to officially launch in October this year.

Taking this opportunity, we had a conversation with Zhuang Ziyang, co-founder of Shengjing Technology, and found that what they want to do is far from just an "AI home-building game." The team is more concerned about whether spaces, like text and video, can be created, distributed, and traded by ordinary people with a low barrier.

​Why go from a B2B space design tool, to a consumer-oriented game?

In 2023, Shengjing Technology was founded in Nanshan, Shenzhen. "Shengjing" means "generating virtual environments," which has been the company's focus from the start—a 3D space generation system. This young team, cultivated by Chinese Academy of Engineering academician Meng Jianmin and Professor Li Zexiang, now has a scale of nearly 100 people, with R&D technical staff accounting for 90%, and has accumulated nearly 100 million yuan in investment from institutions including Nanshan State-owned Assets and Sequoia China.

Zhuang Ziyang told Game Art that the team initially had no plans to make a game; they were developing a set of AI space design tools aimed at the B2B market.

In the traditional interior design and architecture industry, a space from design to realization typically requires a complex process including modeling, placement, modification, and rendering—long cycle times, high costs, and heavy reliance on professional skills. What the team wanted to solve was this very practical pain point: using AI to industrialize "one-click space design."

As a result, early on, Shengjing Technology mainly served home furnishing brand clients such as Panasonic and Nature Home. The real motivation for the team to shift to the consumer side came from user feedback.

The team estimates that about 70 to 80 million young people rent apartments each year and have the need to decorate their rooms. However, professional software like 3ds Max has a high barrier, making it difficult for ordinary users to complete designs on their own. On platforms like Xiaohongshu, a large amount of content has emerged where users share room designs and seek space renovations. There are also many young users who don't necessarily have real renovation needs but enjoy the fun of designing and creating ideal spaces.

The team thus realized that a space creation tool that is simple enough and gamified enough might have a larger user base than professional tools.

During this process, more user feedback validated the feasibility of the product direction: when the product was still positioned as a tool for the home furnishing industry, the related account had only a few thousand followers; after shifting to a consumer-oriented design tool, followers grew to about 50,000; after further turning it into a game, the follower count quickly exceeded one million.

"We spent zero on traffic acquisition—it's still because young people genuinely love it and want to play this kind of AI simulation home game," Zhuang Ziyang said.

Currently, SenBOX's target user profile is predominantly young women under 25, a conclusion drawn from the team's analysis of tag data on platforms like Xiaohongshu and Douyin.

In Zhuang Ziyang's view, a good digital home must first evoke emotional resonance, which is why the product chose the 3D realistic style of "home" as its entry point.

"Home is the easiest space for users to form an emotional connection. If you arrange an office or a forest, users' desire for expression might not be as strong. With the current popularity of 'homebody culture,' people spend a third of their time at home. Starting from the needs and experiences of simulating real life has a lower barrier, and users can understand it more easily."

SenBOX's current user comment section is like a small cultural sample. Some are maximalists who like to fill their rooms with stuff, while others pursue minimalism; some are obsessed with Bauhaus style, others prefer cream style or cyberpunk style... Different MBTI types and zodiac signs also have their preferred room layouts, and some pay attention to Feng Shui.

Shengjing Technology is continuously drawing inspiration for product iteration from these personalized feedbacks.

​Spatial model, letting AI understand the order between objects

SenBOX's current core gameplay is "one-sentence generation." After the space is generated, users can drag, drop, edit, and fine-tune; they can also take photos to convert real objects—like figurines or water bottles—into 3D assets and place them into the virtual space, creating a connection between virtual and real.

When AI handles the tedious basic placement work, users can focus their energy on aesthetics and content creation. For example, a beautiful house needs 300 pieces of furniture; AI can first help users place 200 basic items, and then users add 100 more and DIY the details.

According to the team's plan, generated spaces will expand from rooms to buildings, streets, and cities. Users will also be able to control and upgrade more components, experiencing gameplay such as visitor socializing, quest bounties, and item collection.

Behind this product roadmap lies Shengjing Technology's ongoing investment in the "spatial model."

Zhuang Ziyang stated that text models solve the order of words, image models solve the order of pixels, and spatial models solve the order of 3D assets like tables, sofas, doors, and windows in space. Each is like a computable symbol containing coordinates, dimensions, properties, materials, and other information; different layouts and room types can combine into a wide variety of styles.

This structured spatial encoding path allows the system not just to "paint" a space at the pixel level but to understand the positional, scale, and functional relationships between objects. According to Shengjing Technology's data, generating a 3D space currently takes only 15 to 20 seconds, with relatively low token consumption.

Regarding practical requirements like circulation and aesthetics in home design, Zhuang Ziyang said the model can already basically understand them. On one hand, comprehensive layout rules refer to tacit knowledge from many furniture brands and designers; on the other hand, it also learns color matching and visual rules in different styles through image data.

It is understood that during the beta phase, SenBOX has generated 1.2 million room states. Every user edit, drag, drop, and rearrangement becomes training data for the model to understand spatial rules, forming a positive data flywheel.

On this basis, Shengjing Technology has also accumulated a million-level 3D asset library, tens of millions of image-text data, and spatial coding experience accumulated through partnerships with home furnishing brands. Zhuang Ziyang expects that in the future, there will be hundreds of millions of space-state data generated by millions of users, and scarcity will gradually increase.

The team's next-stage goal is to achieve deeper interaction between humans and spaces, such as allowing virtual characters to understand "how to pick up a cup and drink water." He estimates this capability will still take one to two years to mature.

Zhuang Ziyang believes that compared to traditional home-building games like Animal Crossing: New Horizons and Xindong Town, SenBOX tries to lower the barrier to creation. Traditional home-building games rely on manual construction, requiring users to invest time in learning operations and accumulating resources, while SenBOX uses AI to complete the basic generation, allowing users to quickly enter the expression and adjustment phase.

This also aligns with the current R&D trend of AI games. AI brings not only content production efficiency but also changes in content diversity and gameplay structure. For example, traditional games have limited levels, but AI can continuously generate 3D content, giving the game world potential for constant expansion.

Moreover, the driving force of traditional games mainly comes from completing tasks and unlocking achievements, while SenBOX hopes to form a loop based on content creation and aesthetic selection among users. When users design rooms around the same theme, comparisons, competitions, and natural selection occur, and high-quality creators gain attention.

Therefore, Zhuang Ziyang prefers to take Roblox as a long-term reference. The similarity is that both aim to create low-barrier, diverse, and high-freedom worlds; the difference lies in the content production foundation. Roblox relies on a developer ecosystem and toolchains, while SenBOX hopes to use AI to turn space generation into an action that ordinary users can complete.

"The world needs people, goods, and scenes to run. People can be users themselves, scripts can be driven by AI and agents to interact with NPCs, and scenes are the problem that has never been well solved before," Zhuang Ziyang said.

SenBOX aims to solve exactly this core problem. Just as in the short video industry, the emergence of CapCut reduced the cost of video creation, allowing ordinary people to become content producers and triggering a huge content explosion, SenBOX hopes to use the same logic to lower the barrier to 3D space creation and boost the supply of 3D content.

​More than just a game, also aiming for space distribution, e-commerce, and data closed loop

Therefore, SenBOX's ultimate direction is not limited to a home-building game; Shengjing Technology wants to build an AI space creation UGC platform.

The team does not shy away from the word "metaverse," but gives a more concrete definition: enough content, low enough barriers to entry and editing, and users can socialize and trade within it.

In Zhuang Ziyang's view, the metaverse concept didn't really take off in the past, and the core issue is not just the concept itself but insufficient content supply and high creation costs. If AI can reduce the threshold and cost sufficiently, the boundary between game worlds and virtual living spaces will blur.

On this basis, SenBOX also plans to establish its own content distribution system. Users can browse 3D space-related content or enter spaces to interact; creators can gain attention through their design abilities, forming an ecosystem similar to that of home furnishing bloggers and space design bloggers on various platforms.

For example, a musician's themed room might evolve into a reusable theme template, and a basketball-themed space could expand into an interest community.

"There will be trending lists. Just as Douyin recommends high-quality content, we will recommend high-quality spaces. In a sense, it's like a space version of Douyin, but carrying the next generation of digital life content," Zhuang Ziyang said.

He further explained that the "space version of Douyin" is more suitable as an analogy for distribution logic rather than copying the short video product form. The platform needs to solve how 3D space content is recommended, entered, reused, and how creators get sustained returns.

In terms of monetization, SenBOX is not limited to in-game purchases. The team stated that as the UGC ecosystem forms, the platform may establish a trading system through virtual asset transactions, brand partnerships with home furnishing companies, advertising, value-added services, etc. Real-life home furnishing brands can enter the virtual space; users can pay for virtual furniture and may also connect to real-world consumption; if creators can drive consumption through space design, they should also receive corresponding incentives.

Currently, among Shengjing Technology's three existing business lines, SenBOX serves as the C-end space creation entry, SenHOME handles space e-commerce and brand connections, and SimHub provides spatial synthetic data for embodied intelligence. The three product lines share a unified spatial model foundation, corresponding to content creation, industrial applications, and robot training data scenarios.

Zhuang Ziyang stated that the longer-term value lies in spatial data. Compared to text and images, real, usable, and structured 3D spatial data has been accumulated for a shorter time and is more scarce. Every placement, adjustment, and edit by users, under authorization and compliance, can feed back into the model, helping it understand spatial rules, and further support B2B businesses like SenHOME and SimHub.

Whether this closed loop can truly succeed still needs validation after the product launches, including whether C-end users are willing to continuously create, whether the creator ecosystem can form stable supply, and whether B2B clients are willing to pay for spatial data and generation capabilities. More than exposure volume, retention rate, creator activity, and transaction conversion will more directly determine SenBOX's ceiling.

When asked about future vision, Zhuang Ziyang said: "We hope that in the future, SenBOX can truly bring people a better life. In the short term, it can solve the needs of home renovation and room decoration; in the long term, it may become part of people's spiritual world."