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The Day “AI” Turned Out to Be 700 Humans:

 

Why Builder.ai Should Make Every US Investor Rethink India Tech — and What to Do Next

by Zohaib Ahmed | 28 August 2025

The headline that broke the spell

In May–June 2025 a London-based startup once touted as a $1.5 billion “AI unicorn” — Builder.ai — collapsed into insolvency after multiple reports revealed a striking truth: the company’s vaunted “AI” app-builder was, in large part, powered by hundreds of human engineers in India doing manual coding and customization behind the scenes. The revelations — followed by bankruptcy filings and press investigations — forced investors, customers and auditors to confront how shallow the “AI” claim really was. business-standard.comBloomberg.comDevOps.com

That single story is what a whole generation of skeptical VCs will point at when they talk about “due diligence” in emerging-market tech investments for years.

Not an isolated freak — there’s a pattern

Builder.ai is the latest high-profile fallout, but it fits a pattern of major corporate frauds, scams, and criminal operations that have either originated in India or depended on India-based operations. A short list with hard numbers:

  • Satyam (2009): Often called “India’s Enron.” The company’s chairman admitted to fabricating bank balances and invoices amounting to roughly Rs 7,000 crore (≈ US$1.4–1.5 billion). The scandal destroyed shareholder value and prompted a global governance reckoning. Wikipediasec.gov

  • Punjab National Bank / Nirav Modi (2018): A massive banking fraud where bogus Letters of Undertaking enabled nearly Rs 13,850 crore (≈ US$1.4 billion) of exposure. The case highlighted weaknesses in internal bank controls and cross-border money flows. Wikipediawww.ndtv.com

  • Tech-support / call-centre scams: Law enforcement and industry reports repeatedly flag India-based call centers as a major hub for global tech-support fraud. The FBI/IC3 and allied agencies have documented tech-support scams that have produced hundreds of millions in losses to U.S. and EU citizens; recent prosecutions and raids in India recovered millions and exposed organized cross-border laundering. (See FBI/IC3 annual reports and joint actions with CBI/Microsoft.) ic3.govThe Official Microsoft Blog

Those examples span decades and forms — accounting fraud, bank fraud, organized cyber scams, and now the mis-representation of core product technology. Together they show recurring fault lines: weak controls, opaque governance, human-intensive work passed off as technology, and exploitative criminal enterprises dressed up as “operations.”

Why the Builder.ai story is especially scary for investors

  1. Technology vapor + revenue optics = investor blindspot. Builder.ai sold a product narrative (“AI builds apps in minutes”) while much of the value was human labor assembled behind a curtain. That’s not a new scam — it’s a model that can scale deception: promising automated margins while hiding human cost. When cash runs low, reality emerges. DevOps.com80.lv

  2. Due-diligence failures on an industrial scale. Major global investors (including Microsoft and sovereign capital) either missed or tolerated warning signs. That suggests due diligence emphasis was on growth narratives and market potential rather than forensic validation of product claims and customer contracts. business-standard.comBloomberg.com

  3. Operational risk concentrated offshore. When core product delivery and a large portion of staff are remote and legally or operationally distant from the investors’ home jurisdiction, it becomes far harder to audit, litigate, or recover value in failure or fraud scenarios. Builder.ai’s Indian workforce was at the center of the story. peoplematters.inDevOps.com

  4. Reputational contagion. A single spectacular failure in a country-dominant cluster (e.g., Bangalore-Delhi tech hubs) can shrink risk appetite for the whole ecosystem, hurting honest founders and the flow of sensible capital — but that’s a consequence of persistent headline risk when governance fails.

“Indian scams” — nuance is essential

Before anyone accuses this post of blanket xenophobia: India is a huge, diverse economy with world-class engineering, thousands of reputable firms, and vital contributions to global tech. The examples above are specific, proven failures or criminal operations — not proof that Indian tech as a whole is crooked. That said, patterns we must treat as real risks:

  • Systemic governance gaps in certain firms/industries that allow financial manipulation. (Satyam is a textbook case.) sec.gov

  • Organized criminal abuse of call-centres and outsourcing infrastructure to run international scams. Law enforcement activity and IC3/FBI reports document scale. ic3.govThe Official Microsoft Blog

  • Hype + easy capital can mask structural weaknesses in startups that rely on low-cost labor rather than defensible IP or product R&D (Builder.ai). DevOps.com

So yes — there are recurring, documented problems. But the right policy response is not to demonize a nation; it’s to redesign how capital flows and oversight works.

Why, pragmatically, the US should pause certain kinds of technology investment into India (and what “pause” means)

You asked “Why US needs to stop investing in tech in India.” I’ll translate that into a practical case for selective pause + stricter rules, which is the reasonable policy implication:

  1. Pause blind, hype-driven investments in unproven “AI” plays. If an Indian (or any) startup’s core claim is revolutionary AI with little verifiable output, VCs and corporate investors must step back until independent tech audits and escrowed deliverables are in place. Builder.ai shows what happens when narrative outpaces verification. business-standard.comDevOps.com

  2. Stop funneling sovereign or public money into opaque structures. Sovereign wealth and public pension funds should adopt stricter gates: mandatory independent product verification, contractual escrow for IP/assets, and on-the-ground governance checks before writing cheques. The cost of an 80% hit on public capital is politically toxic.

  3. Freeze investments tied to offshore operational control when product claims are untestable. Where a startup’s value depends on unobservable processes (e.g., “neural network X generates code end-to-end”), require code escrow / third-party verification / reproducible demos in investor-controlled environments.

  4. Temporarily restrict venture financing of companies with histories of regulatory or legal red flags until remediations are visible and validated by independent auditors.

These are not anti-India policies — they are risk-management, structural responses. They raise the bar for trustworthy founders, protect honest startups’ reputations, and reduce taxpayer and investor losses.

Counterarguments (and why they don’t invalidate caution)

  • “India is too important to decouple.” True. India’s developer pool, market size, and technical talent are strategic assets. Cutting all flows would be self-harmful.

  • “Stopping investments is protectionist and punishes the honest.” That’s why the recommendation is selective pause and strict safeguards, not blanket embargo. Aim: raise the cost of deception, reward genuine technical differentiation.

Practical investor checklist — how to invest in India without getting burned

(Use this as your pre-funding checklist for any offshore tech deal.)

  1. Technical reproducibility: Insist on reproducible technical demos, in investor-controlled environments, with audited data pipelines. No demo? No deal. DevOps.com

  2. Code & IP escrow: Mandate code escrow and source-deposit conditions that trigger on insolvency or fraud allegations. (Several buyers now demand this after Builder.ai.) codekeeper.co

  3. Customer contract verification: Independently validate a statistically significant sample of client contracts and delivery receipts; call customers. (Many “growth” figures fail simple spot-checks.) Bloomberg.com

  4. On-the-ground audits: Use third-party forensic accountants and local legal teams to audit bank flows, payroll, subcontracting. (Satyam and PNB show how creative accounting hides risk.) sec.govwww.ndtv.com

  5. AML/KYC & anti-scam diligence: For investments tied to call centers, support desks, or remote access services, require anti-fraud certifications and independent testing against tech-support scam playbooks. (FBI/IC3 data is explicit here.) ic3.gov+1

Policy moves Washington (and big corporates) should make — fast

  • Mandatory third-party technical attestation for AI startups seeking significant US investment, with penalties for misrepresentation.

  • Conditional public investment: tie any public or sovereign fund investment to escrow and escrowed IP safeguards.

  • Enhanced cross-border law enforcement cooperation: expand the FBI/DOJ-CBI channels and make extradition/mutual legal assistance faster for tech fraud. (Ongoing work is already visible.) The Official Microsoft Blog

  • Investor transparency rules: require funds receiving capital from U.S. public entities to disclose on-the-ground verification steps for major offshore deals.

Final diagnosis — stop, but not burn bridges

Builder.ai is a watershed moment — a forensic lesson that hype can mask human-intensive deliverables, that governance matters as much as product, and that capital deployed without rigorous verification is a systemic risk.

So yes: the U.S. (and US investors) should stop the kind of permissive, hype-driven investing that ignores product verification and governance. That means pausing and hardening the process — not slamming the door on India. If anything, higher standards will push more high-quality founders to build defensible technology, strengthen governance, and make the Indian tech ecosystem healthier in the long run.

Sources & further reading (pick of the most important)

  • Business Standard — “Builder.ai faked AI with 700 engineers, now faces bankruptcy and probe.” business-standard.com

  • Bloomberg — investigations into Builder.ai’s alleged inflated sales and business with VerSe. Bloomberg.com

  • DevOps / Tech analysis — coverage of Builder.ai’s collapse and operational model. DevOps.com

  • SEC / Reuters / academic summaries on Satyam (2009) — the ~$1.4–1.5bn accounting fraud. sec.govKnowledge at Wharton

  • NDTV / Wikipedia — Punjab National Bank / Nirav Modi PNB scandal (≈ Rs 13,850 crore). www.ndtv.comWikipedia

  • FBI/IC3 and US Treasury reports on tech-support and call-centre fraud: IC3 Annual Reports and NMLRA notes on growth of call-center fraud. ic3.govU.S. Department of the Treasury

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