AI or just Indonesian fishermen? VCs Say eFishery Took a Page from Builder.ai

BANDUNG - In a stunning revelation similar to UK’s Builder.ai's playbook of employing 700 engineers to manually perform what clients believed was AI work, investors have discovered that Indonesian aquatech startup eFishery used the exact same strategy - except they hired traditional fishermen equipped with nets and a really good WhatsApp group chat to manually catch fish for clients who thought they were paying for "AI and tech powered fishing solutions."

The discovery came to light when Qatar Investment Authority, a major investor in Builder.ai, and Singapore's Temasek Holdings, which backed eFishery, held a Sovereign Wealth Fund Tech Disasters Summit to compare notes on their tech investments.

"Turns out, just like Builder.ai hired hundreds of engineers to manually code what they claimed was AI-generated, eFishery hired hundreds of fishermen to manually catch what they claimed was algorithmically optimized."

"We started noticing some interesting parallels between Builder.ai's 'AI engineers' and eFishery's 'algorithmic fishing solutions,'" said a source close to both sovereign wealth funds. "Turns out, just like Builder.ai hired hundreds of engineers to manually code what they claimed was AI-generated, eFishery hired hundreds of fishermen to manually catch what they claimed was algorithmically optimized."

According to leaked internal documents, eFishery's revolutionary "machine learning fish prediction models" were actually Pak Budi, a 67-year-old fisherman from Lampung, who could predict fish movements by looking at water color and wind patterns. "I've done this countless times in my usual pond until someone from eFishery approached me," said Pak Budi.

The company's "automated aquaculture management system" was revealed to be a network of experienced fish farmers who received customer requests via a custom app and then... went fishing the old-fashioned way.

In response to the revelations, Danatara issued a statement: "We're grateful we dodged this bullet. While our neighbors learn from their mistakes, we've been busy identifying the next billion-dollar unicorn. Probably”