The Rise and Fall of Builder.ai: Lessons from AI Washing, Financial Mismanagement, and the GenAI App Development Market

Builder.ai, a UK-based startup once hailed as a near-unicorn with a $1.5 billion valuation, promised to revolutionize app development through artificial intelligence (AI). Its dramatic collapse into bankruptcy in May 2025 has sparked discussions about the perils of “AI washing,” financial mismanagement, and the state of the generative AI (GenAI) market for app development. Drawing on insights from a former Builder.ai employee who visited Hong Kong, this article explores what Builder.ai was, the reasons behind its failure, the current GenAI market situation in light of its AI washing, and comparisons to the dot-com bubble of the late 1990s. The analysis reveals critical lessons for startups, investors, and the broader tech ecosystem.

What is Builder.ai?

Founded in 2016 as Engineer.ai by Sachin Dev Duggal, Builder.ai aimed to democratize app and website development through a no-code/low-code platform powered by AI. Marketed as a tool that allowed non-technical users to create custom apps as easily as “ordering a pizza,” the company’s flagship AI assistant, “Natasha,” was touted as capable of autonomously handling app development using modular code libraries and automation. Headquartered in London with significant operations in India, Builder.ai raised over $450 million from high-profile investors, including Microsoft, Qatar Investment Authority, and SoftBank, achieving near-unicorn status.

According to a former Builder.ai employee who spoke in person during a visit to Hong Kong, the platform was indeed capable of developing apps, particularly for simpler use cases. However, complex projects (for example, integrating other third-party solutions) required significant human intervention, with engineers in India assisting with integration and customization. This reliance on human labor, while practical, was at odds with the company’s AI-driven marketing narrative, setting the stage for accusations of AI washing.

Why Did Builder.ai Fail?

Builder.ai’s bankruptcy in May 2025 was a culmination of operational, financial, and strategic missteps, rather than a failure of its AI technology alone. Below are the key reasons for its collapse, combining my comments, the former employee’s insights and public reports.

  1. AI Washing and Misrepresentation
    Builder.ai heavily marketed its platform as AI-powered, but a 2019 Wall Street Journal report revealed it relied extensively on human engineers in India, with ~700 staff in Noida and Bangalore mimicking AI responses to maintain the illusion of automation. Internal documents showed executives instructed employees to hide human involvement, emphasizing “proprietary AI” in investor pitches. While the former employee confirmed the platform could develop apps, the need for human engineers to handle complex integrations contradicted the AI-centric branding, eroding customer and investor trust. A 2025 Pragmatic Engineer article clarified that Builder.ai used LLMs like Claude for code generation, but overstated its automation capabilities, contributing to the AI washing narrative.
  2. Financial Mismanagement and Inflated Revenue
    The former employee emphasized that Builder.ai’s failure stemmed primarily from business and financial operations, not its AI products. The company engaged in a “round-tripping” scheme with Indian firm VerSe Innovation, exchanging invoices for unrendered services to inflate revenue by up to 300%. For instance, 2024 revenue was reported as $220 million but revised to $55 million after audits, and 2023 figures dropped from $180 million to $45 million. This led to a loss of investor confidence and a default when creditor Viola Credit seized $37 million, leaving Builder.ai with only $5 million in restricted funds. High debts to Amazon ($85M) and Microsoft ($30M) further strained finances, as noted in a 2025 Business Standard report.
  3. Poor Product Quality and Customer Experience
    Despite its app development capabilities, Builder.ai often delivered buggy, non-customizable apps requiring manual fixes, failing to meet enterprise needs for scalability or security. Trustpilot reviews highlighted billing issues, delayed or undelivered projects, and poor support, with ~25% of reviews being one-star. The former employee acknowledged that complex apps needed human engineers for integration, which sometimes led to delays or quality issues. Legal disputes and refund demands further damaged the company’s reputation.
  4. High Vendor Lock-In Risks
    Builder.ai’s apps were built and hosted on its proprietary infrastructure, creating significant vendor lock-in. When the company collapsed, non-technical customers struggled to migrate or maintain their apps due to limited source code access, as discussed in a 2025 Reddit thread. This underscored the risks of relying on a single provider without transparent code access.
  5. Leadership and Governance Failures
    Founder Sachin Dev Duggal, self-styled as “Chief Wizard,” faced scrutiny for questionable financial practices and was named in a 2024 money laundering investigation in India. He resigned as CEO in February 2025, replaced by Manpreet Ratia, who couldn’t reverse the financial decline. The board’s failure to conduct thorough due diligence and the company’s over-expansion into Southeast Asia and the Middle East increased its burn rate, exacerbating financial strain, as reported by TechSpot in 2025.
  6. Market Competition and Lack of Differentiation
    Builder.ai faced intense competition from established no-code/low-code platforms like Bubble, Adalo, OutSystems, and Microsoft Power Apps, which offered better stability and support, per a 2025 The Next Web article.
  7. Over-Reliance on AI Hype and FOMO Investing
    Capitalizing on the post-ChatGPT AI boom, Builder.ai attracted investors driven by “fear of missing out” (FOMO). Insufficient due diligence by investors like Microsoft failed to uncover overstated capabilities and financial irregularities, leading to losses when the company collapsed, as noted in TechCrunch (2025).

Current GenAI Market Situation Post-Builder.ai

Builder.ai’s failure has not derailed the GenAI market for app development but has reshaped its trajectory, emphasizing transparency and sustainability. Below is the current market situation as of June 21, 2025.

  1. Robust Growth and Investment
    The GenAI market continues to thrive, with global private investment rising from $3 billion in 2022 to $25 billion in 2023, projected to reach $40 billion in 2024 and $150 billion by 2027 (CB Insights). McKinsey’s 2024 Global Survey shows 71% of organizations use GenAI in at least one function, with software engineering a top use case. Tools like GitHub Copilot, AWS CodeWhisperer, and Tabnine accelerate coding, prototyping, and UI design, adding significant value (e.g., $310B annually for retail).
  2. Lessons from AI Washing
    Builder.ai’s exposure as AI-washing has made enterprises and investors wary, demanding clarity on AI versus human roles. The company’s collapse, with its overstated automation claims, has pushed the market toward platforms that balance AI with human oversight, as seen in competitors like OutSystems. A 2025 VentureBeat survey found 60% of tech executives believe over half of AI startups exaggerate capabilities, highlighting trust issues.
  3. Challenges and Risks
    A 2025 S&P Global report notes 42% of AI initiatives were scrapped in 2025, up from 17% in 2024, due to high costs, data privacy risks, and unclear value. Builder.ai’s $85M AWS debt reflects these cost challenges. Poor data quality and governance hinder 80% of AI projects, requiring robust frameworks like Informatica’s IDMC. Vendor lock-in, as experienced by Builder.ai’s customers, has driven demand for open-source models (e.g., Llama 3.1).
  4. Competitive Ecosystem
    The GenAI app development market features infrastructure providers (Nvidia), model developers (OpenAI, Google), and application platforms (Bubble, Adalo). Unlike Builder.ai, these players offer transparent solutions. Smaller, cost-effective models like GPT-4o-mini reduce computational costs, countering Builder.ai’s resource-heavy approach. Market concentration favors giants, marginalizing undifferentiated startups.
  5. Future Opportunities
    Agentic AI, which autonomously handles complex tasks, is gaining traction (e.g., IBM watsonx.ai), promising reliable automation unlike Builder.ai’s pseudo-AI. Human-centric applications, like intuitive UI design, are expanding GenAI’s appeal. Upskilling initiatives address job displacement risks, with 44% of skills expected to be disrupted by 2028 (McKinsey).
  6. Regulatory and Ethical Shifts
    Builder.ai’s AI washing has amplified calls for regulation, with the EU AI Act (2024) and China’s AI laws aiming to curb misleading claims. Environmental concerns about LLM computational demands are pushing companies toward energy-efficient models, a factor Builder.ai overlooked.

AI Washing and the Dot-Com Bubble: A Comparison

The dot-com bubble (1995–2001) saw speculative investment in internet companies, many lacking viable models, leading to a $5 trillion market crash by 2002. AI washing in the current AI boom, exemplified by Builder.ai, shares striking parallels with this era.

Why AI Washing is Common

AI washing is prevalent due to:

  • Hype: ChatGPT’s success fueled AI’s $15.6–$25.6T potential (McKinsey), pushing companies to label products as AI-driven, as Builder.ai did with Natasha.
  • Loose Definitions: AI’s broad scope allows basic tech to be branded as AI, unlike regulated industries.
  • FOMO: Investors poured $25B into AI in 2023, overlooking Builder.ai’s inflated $220M revenue claims.
  • Customer Demand: 76% of enterprises plan AI adoption by 2025 (Gartner), pressuring firms to claim AI capabilities.
  • Competition: Builder.ai exaggerated AI to compete with Bubble, mirroring market saturation.
  • Weak Regulation: Nascent AI laws enable bold claims, as Builder.ai faced no penalties until bankruptcy.

Commonalities with the Dot-Com Bubble

  1. Overhyped Promises: Dot-coms like Pets.com ($82.5M raised, failed 2000) promised internet-driven revolutions, while Builder.ai touted AI app development but relied on humans.
  2. Speculative Investment: Webvan’s $375M raise despite no profits mirrors Builder.ai’s $450M from FOMO-driven investors.
  3. Unsustainable Models: Boo.com’s $135M website flop parallels Builder.ai’s $85M AWS debt and round-tripping.
  4. Market Saturation: Multiple pet e-commerce sites in the 1990s resemble AI startups claiming similar GenAI capabilities.
  5. Gullibility: Public belief in the internet’s transformative power echoes AI optimism, enabling Builder.ai’s facade.
  6. Market Correction: The 2001 NASDAQ crash (48% survival rate by 2004) aligns with Builder.ai’s 2025 bankruptcy, signaling an AI mini-correction (42% AI project failures in 2025).

Differences

  • Tech Maturity: The internet was nascent in the 1990s, while AI leverages mature ML and computing, reducing the scale of AI washing.
  • Regulation: Dot-coms faced minimal oversight, but AI regulations (e.g., EU AI Act) may curb washing faster.
  • Economy: The dot-com crash caused a recession, while AI operates in a resilient tech economy, limiting systemic risks from failures like Builder.ai.

Shared Lessons

  • Due Diligence: Builder.ai’s round-tripping and Pets.com’s logistics failures highlight the need for scrutiny.
  • Transparency: Honest AI claims, unlike Builder.ai’s facade, build trust, as Amazon’s survival showed.
  • Sustainability: Profitable models outlast hype, as Builder.ai’s $37M seizure and Webvan’s collapse prove.
  • Corrections Foster Innovation: Amazon and Google survived the dot-com crash; OpenAI and Google may thrive post-AI corrections.

Conclusion

Builder.ai’s rise and fall encapsulate the dangers of AI washing and financial mismanagement in the GenAI app development market. While its platform could develop apps, as confirmed by a former employee, its reliance on human engineers for complex tasks and overstated AI capabilities led to distrust. The company’s bankruptcy was driven by inflated revenue, high debts, and poor governance, not AI product failures. The GenAI market remains robust, with $40B projected investment in 2024, but Builder.ai’s collapse has pushed for transparency and sustainability. Parallels with the dot-com bubble underscore the risks of hype-driven investment and unsustainable models, yet the AI market’s maturity suggests a more resilient future. For startups and investors, Builder.ai’s failure is a stark reminder: innovation requires substance, not just buzzwords.


About Sammy Fung

With over 20 years of experience in international information technology, promoting the development of open source and open data. and participated in numerous media interviews on technology issues.

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