Exposed: $1.5B AI Startup Was Just 700 Indian Engineers Behind the Curtain

Builder.ai was supposed to be the future of software development. Founded in 2016 by Sachin Dev Duggal, the London-based startup promised a world where building apps was as simple as describing them. Users could type what they wanted, and the platform’s AI assistant—branded as “Natasha”—would take care of the rest, generating apps automatically, without needing a single line of human-written code.

It was a compelling story. The company positioned itself as an AI-powered no-code solution that would democratize software creation, drastically reduce costs, and replace the need for large development teams. Investors bought in. Big names like Microsoft, SoftBank’s DeepCore, and the Qatar Investment Authority poured more than $450 million into the company.

By 2022, Builder.ai was valued at $1.5 billion. It had rebranded itself from “Engineer.ai,” expanded globally, and was featured in headlines as a breakout star of the AI boom. It sold the dream of replacing traditional software development with automation.

But that dream wasn’t real. Behind the sleek demos and polished pitch decks was something far more ordinary—and far more problematic.

Builder.ai Vision

Builder.ai launched in 2016 with a bold claim: app development without developers. The startup said it had built an AI assistant called “Natasha” that could design, build, and deploy software products using natural language input.

Its marketing positioned the company as a no-code platform powered almost entirely by artificial intelligence. Users would describe their app idea, and Natasha would handle the rest—no technical expertise needed.

The story was compelling. It fit perfectly into the growing hype around generative AI. And it attracted major backers, including Microsoft, SoftBank’s DeepCore, and the Qatar Investment Authority.

By 2022, Builder.ai had raised over $450 million and reached a $1.5 billion valuation. It branded itself as a category leader in AI-led software development.

But there was one problem: the AI wasn’t doing the work.

What Was Actually Happening

Internally, Builder.ai operated like a traditional outsourcing firm. The platform was a front-end for collecting client requirements. But actual app development was carried out by around 700 human engineers, mostly based in India.

Former employees say the AI component was minimal. It helped generate quotes and mockups, but the code itself was written manually. There was no true automation.

Clients believed they were buying an AI-generated product. In reality, they were paying for offshore development teams disguised as artificial intelligence.

The company’s internal tools may have improved efficiency, but they were far from the autonomous AI builders the brand promised.

Whistleblowers and internal documents confirm: the AI pitch was a marketing strategy—not a technical reality.

Red Flags and Early Warnings

Concerns around Builder.ai’s claims date back to 2019, when The Wall Street Journal reported that its AI abilities were overstated. Most development, even then, was manual.

But investors didn’t seem to care. Funding continued to pour in. Builder.ai’s branding was slick. The product demos were polished. The AI narrative was too attractive to question.

In early 2024, things started to unravel. New CEO Manpreet Ratia replaced founder Sachin Duggal in an effort to restore investor confidence.

He soon discovered that Builder.ai had been claiming $220 million in 2024 revenue, while actual earnings were closer to $50 million.

This triggered a financial audit—and everything started falling apart.

The Financial Collapse

After the audit, creditor Viola Credit seized $37 million from Builder.ai’s accounts. The company was left with only $5 million, most of it tied up in restricted funds.

With cash frozen and no new investment, operations came to a halt. Offices across the UK, US, India, and UAE shut down.

Builder.ai failed to pay staff, resulting in nearly 1,000 layoffs globally. Projects were paused mid-delivery. Clients were left in limbo.

At this point, Builder.ai had officially stopped functioning as a business. The leadership began Chapter 7 bankruptcy proceedings in the U.S. and similar filings in India and the UK. Its valuation had collapsed from $1.5 billion to zero in less than 12 months.

Things got worse when former COO Robert Holdheim sued the company for $5 million. He claimed he was fired after flagging unethical practices to the board.

The lawsuit revealed that Builder.ai was knowingly misleading investors and clients. Phrases like “80% of code is AI-generated” were repeated in sales decks—even though there was no functioning AI engine.

Then came accusations of round-tripping: Builder.ai reportedly exchanged fake invoices with Indian tech firm VerSe Innovation to inflate its revenue figures.

Bloomberg reported that roughly $60 million worth of invoices were traded without real services being exchanged. VerSe denies any wrongdoing and claims the transactions were legitimate.

Regardless, the U.S. Department of Justice is now investigating Builder.ai for financial misconduct and investor fraud.

Reflexiones finales

Builder.ai’s downfall is part of a larger trend in the AI startup world—something critics now call “AI washing.” It’s the practice of overhyping simple automation or outsourced services by labeling them “AI-powered.” Investors, eager to bet on the next ChatGPT, often fail to dig deeper.

In Builder.ai’s case, the gap between the marketing and the reality was massive. But it’s far from the only startup blurring that line.

As generative AI continues to dominate tech narratives, more scrutiny is expected. Investors are beginning to demand proof of actual AI capabilities, not just pitch decks and buzzwords.

Builder.ai didn’t fail because AI is a bad bet. It failed because it pretended the technology was real before it existed. Its team built an impressive frontend experience, a strong brand, and a compelling story—but it wasn’t backed by working AI.

For clients, the fallout means lost money and broken contracts. For employees, it’s mass layoffs after years of hidden truth. For the AI industry, it’s a wake-up call.

The lesson is simple: if you claim to be building AI, build it—don’t just hire 700 engineers and hope no one notices.