Ujjwal Jain, who led PhonePe's stock broking app Share.Market until May 2026, has launched Atyx.AI, a wealth management startup targeting affluent Indians. He is building it with Debopam Bhattacharjee, a former senior researcher at Microsoft who holds a PhD in computer systems from ETH Zurich.
The Bengaluru company, incorporated in June 2026, is bootstrapped. Jain declined to share product details but said the startup will reimagine wealth management for an AI-first era, moving away from the industry's traditional focus on product distribution.
Why Jain thinks AI has finally caught up
"I've spent more than 15 years building financial infrastructure from every angle — globally at hedge funds, domestically across institutional, retail, and now private wealth. Atyx is the one I'm most excited about, because for the first time, AI has actually caught up to what private wealth in India needs," Jain told Inc42.
The statement is a bet that large language models and machine learning tools can now handle the complexity of portfolio construction, tax optimization, and client communication that private wealth management demands. Until recently, that work required human relationship managers who could juggle regulatory constraints, family dynamics, and bespoke investment mandates.
Jain sees the opportunity in flipping the business model. "This industry for a long time has been built around the distribution of products," he said. "There's a massive opportunity to build in this space from the ground up for an AI-first world."
The team's track record
Jain founded WealthDesk in 2016, an app that let retail investors buy curated baskets of stocks and ETFs. He also built OpenQ (Quantech Capital), the quantitative research infrastructure that powered WealthDesk. Walmart-backed PhonePe acquired both companies in 2022 and brought Jain on to run Share.Market.
Bhattacharjee, CTO and cofounder, spent nearly five years at Microsoft Research before leaving to start Atyx.AI. He and Jain were batchmates at Jadavpur University.
Context on Jain's former employer and its financial trajectory
What we don't know yet
Atyx.AI has not disclosed its product, pricing, or go-to-market strategy. The term "affluent customers" is vague. In India, wealth management firms typically define this as individuals with investable assets between ₹50 lakh and ₹5 crore, while "high net worth" starts above ₹5 crore. Which segment Atyx targets will shape its unit economics and competitive set.
The company is also bootstrapped for now, which limits runway. Wealth management platforms need regulatory licenses, compliance infrastructure, and trust. Building that without external capital is possible but slow.
Logicity's Take
Jain's claim that AI has "caught up" to private wealth is the crux. Existing robo-advisors like Scripbox, Groww, and INDmoney automate retail investing but struggle with the bespoke mandates affluent clients expect. If Atyx.AI can use LLMs to handle client discovery, generate compliant recommendations, and manage multi-asset portfolios, it could undercut traditional wealth desks on cost. The test will be whether affluent Indians trust an AI-first platform with portfolios that often involve illiquid assets, family offices, and tax structuring. Competitors to watch: Dezerv (raised $32M), Kristal.AI (Singapore-based, serving Indian NRIs), and Neo Asset Management.
The broader context
India's wealth management market is expanding as household savings shift from fixed deposits and gold to equities and mutual funds. SEBI's 2024 regulations tightened mutual fund expense ratios, squeezing distributor margins and pushing platforms toward fee-based advisory models. An AI-first approach could reduce the cost of delivering personalized advice, making fee-based models viable for a larger segment.
Whether Atyx.AI can execute on that promise remains to be seen. The name, derived from the Sanskrit word "ati" meaning "beyond," signals ambition. The product will determine if it is warranted.
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Source: Inc42 Media / Gaurav Bagur
Manaal Khan
Tech & Innovation Writer
Produced with AI assistance and reviewed by the Logicity editorial team. Learn more in our Editorial Policy.
