In early 2024, a Singapore-based AI startup made headlines across the region, not for a breakthrough, but for a scandal. Vizzio Technologies, a firm widely touted for building digital replicas of cities using artificial intelligence, had just been exposed for something far more mundane: its founder had faked a doctorate from Cambridge University, and its list of major government clients was heavily embellished. The company’s technology was real, but its story had been inflated, and its leadership’s credibility was thrown into question.

Vizzio is far from the only case. Across Southeast Asia, a troubling pattern may be emerging: AI startups—often the darlings of investors and media—are being scrutinised for overstating their technological capabilities. Some continue to operate despite missteps. Others, like Indonesia’s eFishery, are facing deeper structural crises after revelations of massive financial misreporting tied to inflated AI-driven narratives. And some, such as Nate, a US-founded company with operations in the Philippines, have shut down altogether, leaving behind regulatory scrutiny and lawsuits.

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These incidents raise fundamental questions about the region’s startup culture, investor due diligence, and the race to capitalise on the booming interest in AI. As Southeast Asia positions itself as a global innovation hub, the rise of “fake AI” startups threatens to undermine credibility across the tech ecosystem. Southeast Asia isn’t known as the most robust region when it comes to regulatory standards and checks & balances, so we’re exploring the potential for this issue and what it means.

The mirage of machine intelligence

At the core of these scandals lies a common theme: companies presenting manual labour or conventional software as cutting-edge artificial intelligence. In many cases, there is a veneer of machine learning or natural language processing, but the core product is often far less sophisticated than advertised.

In the case of Vizzio Technologies, founder Jon Lee (who also went by the name Dennis Lee) was found to have faked a Cambridge PhD in computer science. His credentials were a key selling point for investors and media, and the company’s website listed over 20 organisations—including Singapore’s GovTech—as clients. A Tech in Asia investigation found many of these organisations were not active clients, with some having never engaged Vizzio at all. While the company’s digital twin technology does exist, the misrepresentation of its reach and leadership severely damaged its reputation.

Meanwhile, in Indonesia, agritech unicorn eFishery became the subject of a forensic audit in late 2024. The company, once valued at over $1.4 billion, had built its business around IoT-enabled fish-feeding machines and a digital platform for aquaculture. These products were often marketed as AI-enhanced, promising efficiency gains and data-driven insights. But according to the audit by FTI Consulting, the company inflated up to 75% of its reported revenue, roughly $600 million, for the first nine months of 2024. Internal data also showed that only 24,000 feeder units were in use, not the 400,000+ previously claimed.

CEO Gibran Huzaifah later admitted in an interview, “We faked the numbers,” stating that he did so to protect the business and its mission to help farmers. His confession drew both sympathy and criticism, but the financial misrepresentation has forced the company into deep layoffs and put its survival in question.

Behind the curtain: Humans posing as AI

Not all fake AI startups rely on false degrees or fabricated revenue. Some simply replace algorithms with human workers and hope no one notices.

That was the case for Nate, a one-click shopping app based in New York but supported by a large workforce in the Philippines. Marketed as an AI-powered tool that could complete e-commerce checkouts automatically, Nate raised more than $50 million and boasted a 97% success rate. In reality, the “AI” was dozens of remote workers manually entering customer data, filling out forms, and placing orders in real time.

The scheme was uncovered by journalists at The Information in 2022, and in 2025, the U.S. Department of Justice charged founder Albert Saniger with fraud. According to federal prosecutors, Saniger knowingly misled investors and customers about the level of automation behind the product, even instructing staff to conceal the human processes involved.

The case has become a legal precedent in what regulators are beginning to call “AI washing”—the practice of rebranding conventional or manual systems as artificial intelligence to attract investment or boost valuation.

Southeast Asia’s trust deficit

While Nate is a global case, its use of a back-end workforce in the Philippines highlights Southeast Asia’s role not just as a breeding ground for AI innovation, but also as a silent enabler of AI illusion. Outsourced labour, flexible regulations, and a relatively high level of tech optimism make the region a complex environment where scrutiny can be inconsistent and due diligence uneven.

Three key factors contribute to this environment:

  1. Investor pressure: Startups across the region are under immense pressure to demonstrate traction and technical sophistication early. This can incentivise founders to overstate capabilities, especially when competing for global capital.
  2. Lack of technical transparency: AI is a broad term that is often loosely defined. Many founders claim proprietary AI without disclosing whether their models are based on open-source tools or simple automation scripts. Without access to the underlying technology, it is difficult for non-technical stakeholders to evaluate legitimacy.
  3. Cultural reluctance to challenge authority: In many Southeast Asian business settings, employees are hesitant to question leadership or expose internal misrepresentation, reducing the likelihood of whistleblower reports that could prevent fraud from escalating.

The cumulative result is a trust deficit. Founders fear that transparency will make them appear weak. Investors hesitate to probe too deeply, lest they risk losing access to a “hot” deal. And regulators are still catching up.

Learning from the missteps

Not all overstatements are outright fraud. But the blurry line between marketing optimism and deliberate deception is under sharper focus than ever.

The cases of Vizzio, eFishery and Supercharge Lab—a Singapore-based startup whose founder admitted to faking a Stanford PhD—highlight a broader issue: personal credibility is often bundled with technological credibility. When founders pad their resumes or fabricate credentials, it undermines the legitimacy of the very technology they are promoting.

What’s needed is not just better technology, but better governance. That includes:

  • Stronger due diligence by investors, particularly in early rounds where hype often trumps evidence.
  • Technical audits or third-party validations for companies claiming proprietary AI capabilities.
  • More accountability for false claims, including regulatory penalties or investor clawbacks where fraud is proven.

Some investors are already responding. Firms such as Sequoia Capital and Temasek, both of which invested in eFishery, have reportedly begun reviewing their internal processes for validating performance metrics and product capabilities during due diligence.

The path forward: From hype to accountability

Southeast Asia’s AI ecosystem is still young. As regional governments pour funds into AI development—from Singapore’s National AI Strategy to Malaysia’s digital economy initiatives—there is both opportunity and risk. While genuine breakthroughs are emerging, the ecosystem must also develop the mechanisms to separate substance from smoke.

To do so, stakeholders—investors, accelerators, media, and even customers—must adopt a more sceptical lens. AI claims should be interrogated, not simply accepted. Metrics should be audited. And perhaps most importantly, founders should be encouraged to be transparent about their technology’s capabilities and limitations.

After all, AI isn’t magic. And building trust in Southeast Asia’s tech ecosystem will require moving beyond illusion and toward measurable, verifiable impact.

The recent scandals are not just cautionary tales, they’re inflexion points. Whether the region chooses to tighten scrutiny or tolerate ambiguity will define the credibility of its AI future.

Editorial note: the information shared is public, and we are not making assertions on any validity of any company’s dealings, products and services in the market.