This Year's AI Entrants Must First Generate Revenue to Secure Funding Opportunities
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Nowadays, hyping concepts to secure funding in the AI industry is no longer viable, as more investors are requiring entrepreneurs to demonstrate profitability first. This is the key takeaway from deep conversations with investors and several AI entrepreneurs. However, we also observed that startups in the strong application layer of AI continue to thrive during this 'investment winter.'
While preparing for the AIGC conference, we noted that Rabbit Show, an AIGC-focused company, has completed its Series D and D+ funding rounds, raising over 100 million yuan. 'We started accumulating expertise in AI much earlier, which is why we’ve achieved our current success,' said Dong Shaoling, founder of Rabbit Show, who remained composed about the funding. Their long-term groundwork has been the foundation of their fundraising confidence.
Rabbit Show began exploring the 'AI-ification' of template generation soon after launching several hit tools, a vision they’ve pursued since their founding in 2014. The company has also maintained deep industry-academia collaborations with Peking University, solidifying its strong foundation in AI.
Over the past nine years, Rabbit Show has independently developed products like communication big data tools, marketing cloud platforms, and digital human tools. These innovations have been widely adopted by enterprise users across industries such as finance, pharmaceuticals, and real estate.
As Dong Shaoling put it, 'New entrants in this niche field this year won’t stand a chance against those with early groundwork and experience.' For Rabbit Show, steady progress step by step is their deepest insight into the AI entrepreneurship landscape.
Next, let's return to the conversation with Dong Shaoling and explore the accumulated experiences and reflections of Rabbit Display over the years. Below, Enjoy:
Jian Shi: How was the overall financing process for you?
Dong Shaoling: The current economic climate is different from the overly optimistic and enthusiastic era of the past. Now, it's more about selecting the best of the best, a mutual agreement between both parties.
From a strategic perspective, I think the overall process was smooth. Tactically, of course, there were challenges. This round of investment was somewhat delayed. Last year, there was a lot of interest from investors, but the pandemic did have an impact, stretching out some collaborations and investments.
Jian Shi: What do you think were the key factors that impressed investors the most?
Dong Shaoling: I believe there are three main points.
First, product feasibility.
From our observations in fundraising, there is no pre-established trust with investors—trust is earned, not given. Simply presenting a flashy product doesn't guarantee funding. More often, investors will consider backing a venture only after it demonstrates feasibility and future potential.
Second, long-term refinement in a vertical market—product uniqueness.
In our niche, our product stands out as a leader. We've successfully served top-tier enterprises in the digital content market with standardized solutions, achieving a customer renewal rate of nearly 130%.
Third, our growth is stable.
Last year, we achieved nearly 60% growth. Even during generally pessimistic times, our performance provided optimistic reassurance.
My personal reflection is that each stage requires building one step at a time. There are no shortcuts—each level of trust must be earned before progressing to the next.
Jian Shi: Where will the raised funds be allocated to?
Dong Shaoling: Our products have always revolved around three aspects of human narrative: interactive experiences, sensory perception, and knowledge understanding.
This might be a bit difficult to grasp for those unfamiliar with the AI industry. Take sensory perception, for example—human senses involve vision, hearing, taste, and smell. Some AI systems can already classify and predict flavors and scents based on input sample data.
These samples include the ingredients, formulations, and preparation methods of food and beverages. Through training, these systems can identify the characteristics of different tastes and scents and predict the flavors and odors of new samples.
It's not hard to imagine that in the future, every possible method will be used to convert human-perceivable, and even imperceptible, information into digital signals for AI to learn.
This is also part of our vision, so we will continue to invest in this core mission, making understanding more universal. Additionally, we aim to better solve the challenge of human sensory understanding, especially in knowledge domains with high barriers.
Jian Shi: It sounds like you've been involved in the AI field for quite some time. How did you transition from H5 tools to focusing on AIGC core content?
Dong Shaoling: We started with H5 and successively launched four popular tools in content production, covering images, videos, games, and interactivity. These tools serve over 15 million government and enterprise users. However, achieving efficient monetization remained an unresolved challenge at the time.
We then explored post-link marketing cloud solutions. The main challenge in this phase was upgrading marketing methods for small and micro-enterprises through extensive user research. To achieve SaaS standardization in private environments, we focused on leading enterprises and found opportunities in the financial sector.
The financial industry has extremely high software requirements with relatively ample budgets. Here, we identified the need for intelligent content, such as displaying different benefits, materials, and products for Group A and Group B.
To meet these needs, financial institutions invest heavily or outsource to traditional financial firms or digital marketing companies, sourcing professionals across more than a dozen roles including front-end engineers, designers, and technical developers.
Since 2018, we've worked to improve efficiency in all types of digital content requiring heavy front-end development. We defined the global fourth-generation front-end trio: no-code tools, low-code tools, and full-code/auto-code tools. In the latter half of last year, we upgraded to an AI-powered quartet.
Currently, in high-end digital content production, our product competitors cannot automatically generate code through the UI design process, while our products achieve this—a unique advantage.
Jianshi: Your field sounds very niche, almost like one many might overlook.
Dong Shaoling: Of course, these are precisely our opportunities, such as the frequently asked questions in the SaaS industry about how to handle renewals and standardize solutions for large clients.
We believe these questions highlight valuable insights. We've successfully tackled challenges that most would dismiss at first glance. This is exactly why we see the opportunity and scarcity in them.
Some investors argue that the customer acquisition cost for small clients exceeds their profitability, rendering the entire sector unviable. However, they might overlook business models like Chanmama's data search platform, which achieves nearly 100 million in profit from 200 million in revenue.
When profitable products emerge, that's precisely where opportunities lie. While others think one step ahead, we consider three or more to seize these opportunities.
If we started gathering AI resources and working on AI this year, we'd certainly miss our chance. Our ideas took shape much earlier. Though dreaming big might seem unrealistic now, our current success stems from having this vision from the outset.
Even if clients have 100 options, our eight-year head start has built trust, seamless collaboration, and a proven track record that gives us a competitive edge. With this advantage, I'm confident partners will choose us without hesitation to drive mutual progress.
Jian Shi: How do you view this year's wave?
Dong Shaoling: The real turning point was actually last November. For years, we struggled with automated content production, automated typesetting, and automated Chinese artistic font generation. After AI's recent explosive growth, we found these challenges no longer pose any scientific barriers.
In the past, AI could only perform specific tasks—it wasn't very intelligent. It was like training a child from birth to tighten screws; by age 18, they'd be excellent at it, but that's all they could do.
Now it's different. AI has moved toward generalization. As long as the model is well-developed, it can write, draw, edit videos, and interact using natural language—all with low human learning curves. The main reason for this year's AIGC wave is its exponentially greater commercial value.
Jian Shi: With everyone riding this AI wave, have you made any upgrades or applications?
Dong Shaoling: We've always had some research in this field, though breakthroughs were limited. We've collaborated with Peking University professors on studies. Last November, it was the professors who first got excited and pulled us into deeper discussions.
During this year's Spring Festival, we first experimented with AIGC digital humans. These digital humans are not the traditional filmed type but are generated directly from a single photo and a voice clip. We produced one million in just two days, which was an exhilarating achievement for our team—something that would have been impossible with traditional filming methods.
Now, we've accomplished this scale in just two days using AIGC technology, signifying a qualitative leap in our future product development.
Interviewer: I recall that at the beginning of the year, many said the market was still active, but now, towards the end of the year, people are saying the market has cooled. How do you view the current market situation?
Dong Shaoling: Indeed, there’s now a lack of major buyers willing to offer high valuations or invest in ambitious dreams. We need to establish a new valuation system, which may come with some growing pains. The current market demands that we continue to deliver value. Economic fluctuations are inevitable, and confidence will waver, but ultimately, things will improve.
For tech companies, Huawei is an excellent benchmark. If you aim to achieve great things, setbacks are inevitable. Whenever we face challenges, we think of Huawei and their journey, which puts our current problems into perspective.