What if the company quietly making OpenAI, Google, Anthropic, and Meta’s models smarter was founded in India?

Turing is one of the companies shaping how AI is advancing. It started in 2018 as a talent platform that found the top 1% of the world’s engineers, became a unicorn in 2021, and then made a bet almost nobody understood at the time.

In early 2022, long before ChatGPT existed, Turing began helping OpenAI improve its models by feeding human expertise directly into training. Today its network of more than four million vetted engineers and domain experts powers the post-training and evaluation work behind the frontier labs, and the company crossed roughly 300 million dollars in revenue while staying profitable, at a 2.2 billion dollar valuation.

Vijay Krishnan is the co-founder and CTO. He was an NLP researcher at Stanford back when almost no one believed that predicting the next word could ever turn into reasoning, and he explains why running a modern model company without human-in-the-loop data is like entering a race with three tyres instead of four. He walks through how a model is actually taught to use software like Salesforce, why coding became the beachhead for every lab, and what changed for Turing the moment Scale AI was absorbed into Meta.

The conversation then turns to the question every founder is now asked in the room. What is your moat against Claude? Vijay’s answer is to go deeper than the frontier labs can reach, into the outcome you own and the context that lives inside an enterprise.

If you are excited about how AI actually gets built, who really trains the models, and how to build a company that survives the labs, this episode is for you.

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