The hairdressing industry has long been a fragmented landscape of independent “mom-and-pop” shops, characterized by chaotic schedules and inconsistent quality. However, the tide is turning as digital transformation reaches the local community level through specialized vertical technology. Vijay Raina, a seasoned expert in enterprise SaaS and software architecture, joins us to discuss how a revolutionary approach—combining self-developed AI technology with a unique joint operation model—is finally breaking the 20% chain penetration barrier. With a focus on standardization and real-time data, this shift is redefining the salon experience by eliminating traditional bottlenecks and creating a replicable model for mass-market beauty services.
Why has the hairdressing industry historically struggled to break past that 20% chain penetration mark, and how did these specific pain points shape the vision for the AI Community Chain project?
To understand why the industry has stayed so fragmented, you have to look at the sheer chaos of a traditional shop floor. For decades, the beauty industry has been a “trillion-scale” market driven by manual labor and the individual “star power” of stylists, which is inherently difficult to scale. When you walk into a typical independent shop, you often see a messy queuing situation where customers wait blindly, sometimes for 30 or 45 minutes, with no clear idea of when they will be served. This lack of a digital reservation system leads to a massive loss of casual customers who simply walk away when they see a crowded lobby. On the operational side, owners are buried in manual paperwork—counting consumables, tracking performance on paper ledgers, and struggling with data deviations that make it impossible to see the real health of the business. He Rui, the founder of Yuejian, recognized these issues from his own journey from a front-line artisan to a chain entrepreneur, realizing that without a standardized technical “spine,” a brand could never grow beyond a few locations. The vision was to replace this reliance on “senior store managers” with a digital system that ensures every customer, whether in a busy downtown hub or a quiet residential community, receives the same high-efficiency, affordable service without the predatory sales tactics that often plague the industry.
You’ve emphasized that this isn’t just another software-only solution but a system “polished in stores.” Could you walk us through how that front-line experience translates into the digital architecture of the SaaS platform?
One of the biggest mistakes tech companies make is building software in a vacuum, but this project flipped that script by insisting that the code be written where the hair is actually cut. We abandoned the “closed-door” R&D model in favor of a path where every feature is battle-tested across 40 offline joint stores before it ever reaches the wider market. This has allowed us to accumulate an incredible wealth of data—including 170,000 precise online members and over 800,000 real service orders—which informs every iteration of the SaaS system. You can see the results in the way the “digital intelligent store inspection” works; it isn’t just a checklist, but a tool that handles material management and staff training based on real-time needs. Because 70% of our product optimizations come directly from the feedback of stylists and joint operation partners, the system feels intuitive rather than burdensome. We’ve created a closed-loop environment where new functions are tested internally, verified for stability, and only then rolled out to ensure that the technology actually solves problems like talent replication and inconsistent technical standards.
Management efficiency and data deviation are silent killers in the service industry. How does the integration of AI and visual data analysis actually change the day-to-day life of a shop manager or a stylist?
In a traditional setting, a manager might spend hours at the end of a shift trying to reconcile how much shampoo was used against how many clients were served, often finding discrepancies that they can’t explain. With our AI-driven visual analysis and SaaS integration, that manual labor is replaced by a transparent, real-time dashboard that tracks everything from consumable inventory to the specific performance metrics of each staff member. For the stylist, the pressure of “selling” is removed because the system handles the online reservation and transparent pricing, allowing them to focus entirely on their craft. The AI customized beauty services even help in providing a tailored experience for the customer, suggesting styles or treatments based on data rather than a hunch. This level of intellectualization means that the operation of the store is no longer tethered to the personal whims or varying skill levels of a single “star” manager. Instead, the system provides a replicable technical standard that allows a new employee to step in and understand the store’s workflow and expectations within a matter of days, not months.
The “joint operation” model you’ve mentioned seems to tackle a major trust issue in the beauty industry regarding capital control. How does this financial transparency empower entrepreneurs who might be wary of traditional franchises?
This is perhaps the most disruptive part of the business model because it addresses the fear of “capital risk” that has historically made entrepreneurs hesitant to join large chains. In the traditional franchise model, headquarters often control all the cash flow, which can lead to disastrous results if the parent company faces financial trouble or mismanages funds. Our joint operation system uses an independent and compliant financial management mechanism where the daily operating cash flow goes directly into the partner’s own account. The headquarters never touches the store’s operating funds; instead, our role is strictly limited to brand standards, technical training, and providing the SaaS backbone. This creates a “lightweight” entrepreneurship opportunity where the practitioner can focus on the local community without worrying that their hard-earned revenue is being pooled into a risky corporate pot. By solving the capital safety problem, we’ve made it possible for small and medium-sized operators to access professional-grade digital tools and brand power while maintaining the financial autonomy they need to feel secure in their investment.
Looking at the momentum from the current Pre-A round, how do you see the balance shifting between the physical chain business and the commercialization of your vertical SaaS for the wider market?
We are currently executing a very deliberate phased growth path that treats the physical stores and the SaaS technology as two sides of the same coin. In the short term, the priority is the implementation of the AI intelligent beauty store model across our existing footprint, ensuring that every community location is fully optimized with the latest iteration of our system. However, as we move into the medium term, we are preparing to fully open our practically verified SaaS system to the public, offering a complete digital management solution to the thousands of independent beauty entrepreneurs who are currently struggling without proper tools. This creates a sustainable “two-way” revenue stream: physical operation income from our community stores and technical service revenue from the B-end market. By the time we reach our long-term goals, we expect to have built a massive offline volume that serves as a living laboratory for our software, allowing us to maintain a technical barrier that pure software companies simply cannot match because they lack the “boots on the ground” operational data that we possess.
What is your forecast for the digital transformation of the community beauty industry?
I believe that by 2028, the “single-store” model without digital integration will be virtually obsolete in urban communities, as consumers will no longer tolerate the friction of blind queuing and opaque pricing. We are moving toward a landscape where “AI+Community” becomes the standard, where your hair appointment is as seamless as ordering a ride-share, and where stylists are empowered by data to provide highly personalized services. The industry’s chain penetration will likely double as digital systems finally provide the standardization needed for large-scale, low-risk expansion. For readers and practitioners, my advice is to stop viewing technology as a “fancy marketing concept” and start seeing it as the essential infrastructure for survival; the winners of the next five years will be those who prioritize stable service standards and safe, transparent financial operations over the flashy, unsustainable promotions of the past.
