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三维家发布会：家居AI落地逻辑解析

来源：家居百科时间：2026年03月10日 15:51

AI in Home Industry: Efficiency, Innovation, and New Opportunities AI in the Home Industry: Revolutionizing Efficiency and Business Opportunities

Over the past two years, the home industry has been struggling with a "sensory mismatch": the cost of traffic is rising while the sales cycle is getting longer; the slogan of digitalization has been shouted for many years, but the pressure of terminal delivery has not decreased.

In the stage of "knife-fighting" in the existing market competition, what companies truly rely on is no longer scale expansion, but efficiency improvement. In other words, who can complete more business in a shorter time with higher efficiency has a greater chance to stand firm in the next round of competition.

Therefore, AI has quickly become the focus of industry discussions.

However, for home industry professionals, anxiety has not decreased due to the outbreak of AI technology, but has become more confused — is AI just a "visual bonsai" at the exhibition, or a "production tool" that can truly run business and generate profits?

On March 5th, Sanweijia's spring conference themed "AI+3D seen as it is", gave an extremely penetrating answer. It's more like an exhibition of industrial path: when the industry is still discussing AI, Sanweijia has already embedded AI into the real home business scenario.

Digital Foundation, AI Acceleration: The New Infrastructure of the Home Industry

Looking back over the past ten years of technological evolution in the home industry, we can roughly see three clear paths: from the tooling era of solving design expression, to the digital era of "design as manufacturing," and to the current AI-enhanced stage driven by algorithms.

In this evolution, digitalization ensures the "certainty" of business processes — it transforms non-standard design into standard industrial parameters, and realizes the lossless transmission of data from the front-end store to the back-end factory; while AI "presses on the accelerator" on this basis, through algorithms to reduce professional threshold, eliminate repetitive labor. In other words, digitalization solves the problem of "whether it can be done," while AI solves the problem of "whether it can be done more efficiently."

From this perspective, the technical path presented by Sanweijia's this release is extremely clear: with the long-term accumulated front-end and back-end integration capabilities as the foundation,叠加 "AI technology flywheel". This logic drives AI iteration through the continuous accumulation of industry data, and AI capabilities improve application efficiency.

When AI Enters the Business Process: Changes in 4 Key Scenarios

The difficulty in the landing of AI in the home industry has never been the technology itself, but the extreme complexity of the scene.

In this release, Sanweijia proposed four solutions — whole home, renovation, whole-home customization, and new business overseas, which almost accurately target the four core incremental tracks in the current industry:

1. Whole Home Solution: Solving Complex Delivery Difficulties with "ViewAI"

The problem in the whole home track is "origin deviation": low measurement efficiency, slow return design, and long customer decision-making cycle. In the traditional whole home chain, the time difference from measurement to drawing for several days is often the peak period for customer loss.

The emergence of AI measurement and real-time modeling attempts to shorten this path. In the whole home track, Sanweijia takes ViewAI as the key tool to solve the problem of measurement efficiency. As the first AI measurement product that connects design in the industry, it realizes measurement to modeling, measurement to design through AI vision and 3D space reconstruction.

At the press conference, the whole home enterprise Jiemu shared the practice case of AI design system in the whole home business. Through AI-assisted design, enterprises can generate multiple whole home solutions in a short time and quickly verify their feasibility for landing.

This allows enterprises to take into account spatial effects, construction feasibility, and cost control in the design stage, thus solving the "impossible triangle" that has existed in the whole home industry for a long time: "good scheme, feasible implementation, reasonable price."

For whole home enterprises, AI is not only an efficiency tool for the design stage, but is also connecting the scattered processes between measurement, design, and delivery, making the chain from generation to landing of the whole home solution more smooth.