A recent bankruptcy announcement from the High Court in London has turned the once $1.6 billion British “AI unicorn” Builder.ai into a case of the “Emperor’s New Clothes” in the history of AI development.
The author notes that Builder.ai was founded in 2016 with a focus on using AI to help businesses build applications. Its Indian-born founder, Sachin Dev Duggal, promoted the slogan “Build apps like ordering a pizza.”
In an era when AI had not yet been commercialized and the No-Code (no-code development) field was just emerging, this concept immediately triggered the investment community. Builder.ai attracted significant investment, securing a total of $450 million, with backing from SoftBank, Amazon, Microsoft, and others.
However, doubts later arose regarding Builder.ai’s core technology. In 2019, it was revealed that most of the code was manually written by Indian programmers, with no AI involved. Additionally, the company was implicated in financial fraud, which directly led to its bankruptcy.
At the end of 2022, the launch of ChatGPT excited AI entrepreneurs and investors, initiating a surge in investment within the AI sector. According to CB Insights, AI accounted for 20% of global venture capital in 2023. Market observers pointed out that Builder.ai’s bankruptcy reflects the industry chaos under the AI investment frenzy, with many similar cases emerging.
“Valuation bubbles in the AI sector are severe, and under capital-driven hype, companies can achieve high valuations based solely on technology concepts,” said an angel investor and senior AI expert. He emphasized that AI startups should prioritize profitability verification, clarify paying use cases early, and focus on cash flow. Technologies should adapt to actual needs, deeply integrate into business scenarios, and prioritize solving customer pain points rather than merely chasing “cool” features.
AI Dependent on “Human Effort”
It is understood that Builder.ai was founded before OpenAI’s rise and early on promoted the “No-Code + AI” concept, which allowed app development without writing code. While this concept is not outdated today, given the popularity of ChatGPT, it was quite ahead of its time in 2016.
From the Indian venture capital scene to Silicon Valley, Builder.ai quickly became a popular “No-Code + AI” company, securing multiple rounds of financing. In 2018, Builder.ai received investment from SoftBank’s subsidiary Deepcore.
In 2021, Builder.ai launched what it called the world’s first AI product manager, Natasha, which could automatically generate 80% of code and create code based on descriptions, causing a stir in the industry.
Afterward, Builder.ai accelerated its financing efforts. By 2022, Builder.ai had raised $195 million. In May 2023, it received an additional $250 million in funding led by the Qatar Investment Authority. That same year, Microsoft endorsed Builder.ai as a strategic investor and partner, and integrated the platform into Microsoft’s cloud services.
At this point, Builder.ai had raised a total of over $450 million, reaching a valuation of approximately $1.5 billion and achieving unicorn status.
However, during the period when Builder.ai gained funding with its “No-Code + AI” concept, doubts arose regarding its AI technology.
A 2019 report revealed that most of Builder.ai’s code was manually written by Indian programmers, rather than being created by true AI. At the time, the company’s founder responded by stating that the company never claimed to rely solely on AI for its products, which indirectly acknowledged that the work was “human” rather than “intelligent.”
Moreover, several former employees revealed that the company used traditional software to handle tasks, with much of the work completed manually by employees. According to several former employees, the so-called Natasha was merely a front-end chat interface, connected to hundreds of low-paid outsourced engineers in Hyderabad, India.
If Technical Fraud Was Builder.ai’s Original Sin, Financial Fraud Was the Final Straw
If technical fraud was Builder.ai’s original sin, financial fraud was the final straw that led to its collapse.
At the end of 2024, the company’s board became suspicious of its operational status and conducted an audit. The investigation revealed that while Builder.ai claimed to have $220 million in revenue in 2024, the actual figure was only $55 million. The reported revenue for 2023 was $180 million, but the true earnings amounted to only $45 million.
Once the financial fraud was exposed, investors rushed to reclaim their investments, leading to a collapse of Builder.ai’s cash flow, forcing it into bankruptcy. Reports indicate that U.S. prosecutors have issued subpoenas to Builder.ai, requesting financial statements and customer lists to investigate its systematic financial fraud.
Builder.ai was forced to file for bankruptcy in mid-May across five locations: the UK, the U.S., India, Singapore, and the UAE. Global projects have been frozen, and the company’s website is no longer accessible. Notably, Builder.ai’s founder, Sachin Dev Duggal, resigned as CEO in February this year. According to the company’s new CEO, the company’s accounts now hold only $5 million, which is restricted and unable to cover payroll.
The Primary Reasons for Builder.ai’s Bankruptcy
“Builder.ai’s bankruptcy was mainly due to technological gaps and flaws in its business model,” said the director of Deep Technology Research Institute. The company’s technology maturity was insufficient, and its “No-Code AI development platform” actually relied heavily on human labor, resulting in inefficiencies and uncontrolled costs. The excessive capital boost (team size increased fourfold after SoftBank’s investment) also led to a collapse in unit economics (customer acquisition costs were 2.3 times the customer value). Additionally, the company’s market share was under 1.5%, with competition from giants like Microsoft’s Power Platform, leading to its eventual cash flow collapse.
The Lack of a Thriving Entrepreneurial Ecosystem in Europe
In reality, Builder.ai’s collapse is just the tip of the iceberg of the “AI washing” phenomenon. In the AI frenzy, investors are often driven by a fear of missing out (FOMO), believing that failing to invest means missing out on the next OpenAI.
The sudden fall of Builder.ai may be one of the most representative events of this era, but it certainly won’t be the last, as many similar cases are expected to emerge.
For instance, earlier this year, AI shopping app Nate, which claimed to automate e-commerce transactions, was exposed for relying on manual operations by outsourced workers in the Philippines. By faking AI process demonstration videos, Nate deceived investors out of $40 million, of which $4 million was misappropriated by the founder to buy a mansion and a private jet.
In the AI investment frenzy, the lack of technical validation and regulatory gaps have provided fertile ground for such scams. To this day, the decision-making processes of deep learning models in AI remain unexplained, making it impossible for non-experts to verify, while pre-recorded “live interaction” videos have become a common industry trick, making it difficult to discern truth from fiction.
“The AI field suffers from severe valuation bubbles. Under capital-driven hype, companies can achieve high valuations based on technology concepts alone, while the logic of profitability is ignored, resulting in a vicious cycle of ‘fundraising—burning money—refunding,'” said the author. He also stated that capital favors short-term returns, which has led to a “scale-first” mentality where companies blindly expand without the ability to generate sustainable cash flow.
The author also noted that Builder.ai’s bankruptcy highlighted problems in the entrepreneurial ecosystem in the UK and Europe, such as market fragmentation, poor exit mechanisms, and talent drain. “In Europe, language and regulatory differences between countries make it difficult for businesses to scale. IPO activity is low, and investors rely on mergers and acquisitions for exits, making follow-up financing challenging. Top AI talent is being poached by high-paying U.S. companies, leading to instability in early-stage teams,” he said.
There are also similar observations. It was pointed out that the entrepreneurial ecosystem in the UK and Europe has structural shortcomings: smaller capital scale (VC financing median is 28% of Silicon Valley’s), market fragmentation (the dispersed markets in EU countries reduce economies of scale), talent loss (AI talent’s annual salary is 40% lower than in the U.S.), and policy delays (GDPR costs account for 20% of operations).
In the author’s view, although there are many limitations in Europe’s entrepreneurial ecosystem, there are still some highlights, such as top technology companies like Google’s DeepMind and Mistral AI.
Regarding the current entrepreneurial ecosystem in the UK and Europe, the author said: “Europe has advantages in data privacy and government research subsidies, but its commercialization capability and capital patience still lag behind the U.S. If Europe fails to optimize early investment mechanisms and break down regional market barriers, it may remain a technology testing ground for a long time, unable to produce global AI giants. Europe needs to strengthen market integration and improve capital patience to nurture more competitive AI companies.”
Some industry analysts believe that the AI sector is undergoing a reshuffling period, and AI entrepreneurship is entering deeper waters. How to find sustainable business models amid intense competition and attract rational investment has become an urgent issue for AI companies today.
Thus, the AI industry’s diverse landscape unfolds: Top AI companies like OpenAI and xAI thrive with the support of “backers” and self-sustaining operations; meanwhile, AI image generation model Stable Diffusion has been rumored to face a cash flow collapse, and the once-popular U.S. AI unicorn Afiniti has already filed for bankruptcy protection.
“The fundamental issue lies not in the region, but in the global AI bubble bursting—when capital retreats, companies with weak technological foundations will inevitably be exposed. Europe must improve its capital patience and market integration capabilities,” the author stated.