Turing Brand Guidelines: A 2018 Remote-Hiring Platform Turned AI Training Partner

Hiring engineers at a distance.

Turing was founded in 2018 by Jonathan Siddharth, its chief executive, and Vijay Krishnan, according to the company, which lists both as co-founders. Its seed round was led by Foundation Capital, the company says, and its Series B, in November 2020, by WestBridge Capital.

The idea was hiring at a distance. TechCrunch reported in March 2025 that Turing began as, in effect, an HR-technology startup whose early product was a platform for vetting and hiring remote coders, a business that took off in 2020 as companies looked for tools to find and manage remote teams. A co-founder of WestBridge told the publication that when he first met the company, in 2018, he was struck by how it set aside the familiar consultancy and offshoring model: no HR staff, just Turing and remote engineers.

The company’s name for that platform was the Talent Cloud. In December 2021 TechCrunch described Turing as using AI to source, evaluate, hire, onboard and then manage engineers remotely, including the HR and compliance side, inside a bigger platform it called the “Talent Cloud.” A backer quoted in the same report used a longer form, the “Intelligent Talent Cloud,” and the company’s own blog refers to engineers sourced “planet-wide.” Most people joined for fixed-term projects, Siddharth told the publication, though some went on to longer or permanent roles with the companies that hired them.

From hiring platform to AI training.

Growth through 2021 was fast by the company’s own count. Siddharth told TechCrunch in December 2021 that the candidate pool had grown ninefold in a year, to 1 million engineers and developers from 140 countries, up from the 180,000 the company had reported a year earlier. The platform then covered some 100 technologies and 15 job titles, from entry-level roles to engineering directors and chief-technology-officer candidates, and the most common requests were for full-stack, front-end, back-end and site-reliability engineers. That month Turing announced a Series D round led by WestBridge Capital, with Foundation Capital, StepStone Group and several others taking part.

Then the work changed. TechCrunch, recounting an earlier report by Semafor, said that in 2022 Siddharth was called to a meeting at OpenAI that he thought would be about recruiting engineers. Instead, researchers there, who had found that code added to training data improved a model’s reasoning, asked Turing to help generate such code. That set off a new line of business, and by March 2025 the publication described Turing as working with a number of foundation-model companies, and with companies building apps on top of large language models, as well as continuing to place engineers.

Siddharth rejected the word “pivot.” He told TechCrunch that Turing still earned substantial revenue from its older business of sourcing coding talent, and that all of its business lines were growing. In his telling, the infrastructure built for hiring coders was what placed the company in the middle of the new work: the same pool of vetted engineers could write the code that AI labs wanted for training.

He also allowed that none of this had been foreseen. “We could not have predicted the ChatGPT moment,” he told TechCrunch in March 2025, adding that few people had understood how important software-engineering data would become for teaching a model to reason and code. In December 2021 the same publication had described Turing’s customers as ranging from technology companies to businesses outside tech that still needed engineers to build and run parts of their operations; by 2025 the list of buyers had widened to the companies training the models themselves.

Talent networks and their language.

Tech-talent networks and developer marketplaces sell access to people, so their identities lean on a few recurring ideas: the size of a pool, the reach of a map and the rigour of a test. Andela says its network speaks more than 300 languages and that more than 650 organisations have built with it; Turing’s website counts more than 5 million domain experts. Such figures are the companies’ own, and they move quickly: in December 2021 Turing told TechCrunch it had 1 million engineers and developers, and in March 2025 it said it worked with some 4 million coders.

Vetting usually gets a name of its own. Turing called its platform the “Talent Cloud,” and Andela later launched the Andela Talent Cloud. English Wikipedia describes Andela’s technical, soft-skills and leadership assessments feeding a “match fitness score,” and Andela has bought assessment and practice tools such as Qualified and Codewars, which it presents as a source of behavioural data from millions of developers.

The matching itself tends to be described as a sequence. TechCrunch wrote in 2021 that Turing used AI to source, evaluate, hire, onboard and then manage engineers remotely, and in the same year described Andela as evaluating technical and soft skills before matching engineers with the teams they fitted most closely.

Corporate pages put founders, investors and milestones up front. Andela’s about page runs a dated timeline of funding rounds, cohorts and acquisitions, illustrated with photographs of its own events, and introduces its leadership team; Turing’s company page lists its two co-founders by title. This guide sets out what can be checked about each company, separating dated reporting from what the company says about itself.

Two divisions and a new mission line.

In March 2025 Turing announced a Series E round led by Khazanah Nasional Berhad, Malaysia’s sovereign wealth fund, with WestBridge Capital, Sozo Ventures, AltaIR Capital and others taking part. TechCrunch then described it as a Palo Alto-based company that said it worked with some 4 million coders around the world, while its own staff numbered in the hundreds, according to one investor. It reported that Turing called its AI-training division “Turing AGI Advancement” and its work on apps and services built on large language models “Turing Intelligence.”

The company now describes itself in other terms. Its website, in November 2026, says Turing is headquartered in San Francisco, gives its mission as “to accelerate superintelligence to drive real economic progress,” and divides its work into Enterprise AI and Frontier AI, the second covering software engineering, enterprise knowledge work and STEM fields. It counts more than 5 million domain experts and lists Krishnan as co-founder and head of growth, alongside Siddharth as co-founder and chief executive.

That shift shows in the language more than in the name. In 2021 the company talked about engineers, job titles and remote teams; by 2026 its pages talk about domain experts, curated tasks and frontier labs. The word “Turing” has stayed the constant across both, a short and familiar name that has served a hiring platform and a supplier of AI training work alike.

For a design guide, Turing shows how a brand can keep one name and one network while the work it sells changes. Compare Andela, which also built a network of remote engineers, and Upwork, an open marketplace for freelance work. For this guide we use an ink blue, a slate grey and a signal yellow with a sans, an unofficial interpretation; no product or logo is reproduced.

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