An AI-Native Attack On The Outsourcing Machine
Hang Ten Systems is an AI-native IT services startup founded by former Infosys CEO Vishal Sikka to show that large enterprises can build, change, and run critical software systems with far fewer humans and far more automation, directly challenging the labor-heavy outsourcing model that has dominated corporate technology work for decades. This is not another neutral AI lab experiment; it is an explicit attempt to attack the unit economics of traditional IT services from the inside. Sikka knows how that machine works, because he spent years running it. Now he is betting that the same automation wave that once looked like a threat can become the core of a new services business built around AI agents, reusable skills libraries, and a far smaller bench of highly specialized experts. The message is blunt: the old model is bloated, and AI-native delivery will expose it.
From Backing OpenAI To Building His Own Disruptor
Sikka’s move matters because of his history. He was at the helm of Infosys when it granted a key early backing to OpenAI, giving him a front-row seat to the gap between promising AI research and large-scale enterprise use. After his acrimonious exit from Infosys in 2017, he spent two years preparing his next act and then founded Vianai Systems in 2019, an enterprise AI company seeded with USD 50 million (approx. RM230 million). That first Vishal Sikka startup focused on human-centered AI, especially in finance, and later partnered with major cloud and services players. Hang Ten Systems is a sharper second strike: instead of helping incumbents add AI to existing processes, it aims to replace the processes themselves. In effect, Sikka is now doing what his old employer once paid him to prevent—using AI to erode the billable-hour engine of the services industry he led.
Hang Ten’s Model: AI-Native IT Services With Teeth
Hang Ten Systems is not pitching vague AI consulting. According to its launch, the company raised USD 32 million (approx. RM147 million) in seed funding led by Mayfield, with Aramco Ventures as a strategic investor and several angels joining in. It already works with Siemens Gamesa Renewable Energy and Fresenius on AI-native project delivery, which means the pitch is being tested inside complex, regulated enterprises. Hang Ten describes its approach as agentic code generation, a reusable skills library, and an expert full-domain engineering bench focused on enterprise transformations across finance, HR, and new product development. You can roll your eyes at some of the jargon, but the target is clear: the same transformation and maintenance projects that global firms have long handed to Infosys, Tata Consultancy Services, and Wipro. As Sikka frames it, this is about helping enterprises “use [AI] as a force to do what no one could do before.”
Why The Timing Terrifies Public Markets
Hang Ten’s launch would be notable in any year; right now it is perfectly timed to amplify existing fear. Indian IT services stocks are already trading under pressure as investors try to calculate how much of their revenue can be automated by AI tools for coding, testing, documentation, and support. One analysis warned that an aggressive scenario of AI disruption could drive another 30% to 65% valuation derating for parts of the sector. This anxiety sits inside a much larger story: reports forecast the broader technology industry reaching around USD 315 billion (approx. RM1.45 trillion), with the software services piece at roughly USD 250 billion-plus (approx. RM1.15 trillion) and “under AI pressure.” Incumbents are scrambling to show they are adapting—signing deals with frontier-model vendors and pitching an AI-first services opportunity worth hundreds of billions by 2030. Hang Ten shows that some of the sharpest Indian tech founders would rather build the disruptor than defend the old margins.
The Real Test: Risk, Trust, And A New Services Narrative
For all the buzz, Hang Ten Systems is still small next to the giants it wants to unsettle. The legacy players have long-standing client relationships, compliance muscle, delivery managers, offshore centers, and years of trust inside regulated enterprises. Hang Ten has USD 32 million (approx. RM147 million), a credible founding team, and an aggressive thesis. The next test is not whether it can sound convincing at launch, but whether it can carry risk when AI-written code breaks a finance workflow, win procurement battles against entrenched partners, and prove that its AI-native IT services model reliably beats bundled promises from incumbents. If it can demonstrate that with Siemens Gamesa, Fresenius, or another large client, the conversation shifts from “can AI do services work?” to “how much of the services model existed only because there was no better tool?” That shift would mark genuine enterprise AI disruption, and it would validate Sikka’s bet that a wave he once helped forecast is now his to ride.
