Two fund managers who handled Rs 1.35 lakh crore for others just built a company for India's rich

Most wealthtech startups are built by engineers who decide finance needs an app. Veriqus was built by two people who spent their entire careers on the other side of that relationship, actually managing money for India's wealthiest families, and walked away from established institutions to build something neither had access to build inside them.

Two very different kinds of credibility, joined together

Veriqus was co-founded by Ashish Gumashta, former Chairman and CEO of Julius Baer India, who spent more than three decades in wealth management and helped establish DSP Merrill Lynch's wealth management business in India from the ground up, and Roshi Jain, a former senior fund manager at HDFC Asset Management Company who managed more than Rs 1.35 lakh crore in assets across three flagship funds, including the widely tracked HDFC Flexi Cap Fund, as of November 2025.

That combination isn't incidental to the company's structure. Gumashta leads Veriqus' wealth management business. Jain heads its asset management division. Between them, the founding team represents both sides of what wealthy Indian families actually need: someone who understands how to advise and manage a family's overall wealth, and someone with a proven, large-scale public track record of actually generating returns.

Building the single platform India's wealthy currently don't have

Veriqus isn't positioning itself as a narrow investment app. It's built as an integrated platform combining wealth management, asset management, business advisory, and lending, aimed squarely at high-net-worth individuals, family offices, entrepreneurs, and institutional clients, the segment of India's economy whose financial lives typically span multiple advisors, multiple institutions, and very little coordination between them.

The wealth management arm is built as a technology and AI-enabled platform, offering tools for portfolio analytics, risk monitoring, client reporting, and decision support, running on an open-architecture model that lets Veriqus offer investment products across public equity, private equity, fixed income, alternative assets, and real estate, delivered through its own team as well as external partners. The asset management division, under Jain, is built around what the company describes as real-economy intelligence and fundamental, long-term research, rather than short-term trading strategies.

Why this raised Rs 387 crore before doing very much yet

In July 2026, Veriqus raised Rs 387 crore (around $40 million) in a funding round led by Norwest Venture Partners, alongside participation from family offices and a handful of ultra-high-net-worth individuals, notable because the company was only recently incorporated, raising this scale of capital essentially at the platform-launch stage rather than after years of proven traction.

Norwest, which manages roughly $15.5 billion globally, framed the investment around India's expanding wealth market and the specific opportunity in underserved Tier II and other high-growth cities, markets Veriqus has explicitly said it intends to prioritise rather than treating as an afterthought to India's metro-first wealth industry.

Why this matters beyond one funding round

Veriqus is a bet on a specific, provable idea: that India's wealth management industry has historically been built around scattered, single-purpose advisors, and that consolidating wealth advisory, asset management, business advisory, and lending under one technology-driven roof, led by people who've actually managed serious institutional money rather than merely built the software layer around it, is worth funding at scale before the product has years of track record behind it.

In a country where the number of wealthy families is expanding well beyond its traditional metro strongholds, Veriqus is betting that being early, and being led by people who've already earned the trust of India's wealthiest families in previous roles, matters more than waiting to prove the model first.