In a recent conversation with Arushi Agarwal from Indian Startup Times, Aaditya Aanand, Founder of Multibagg AI and a standout entrepreneur from Shark Tank India Season 5, spoke candidly about his journey from a small town in Bihar to building an AI-first fintech platform aimed at fundamentally changing how India’s retail investors make decisions.

Forged in a Small Town, Built with Mental Strength

Aaditya Aanand’s story doesn’t begin in boardrooms or startup accelerators. It begins in Munger, Bihar, a town where scarcity was part of everyday life. Growing up with limited resources shaped something far more enduring than financial ambition, it built resilience.

That early exposure to hardship, Aaditya explains, gave him emotional stability that many founders struggle to develop later in life. Having seen uncertainty early on, he learned not to overreact to either success or failure. This calm, often mistaken for detachment, has become one of his defining strengths as a founder.

From IIT Kanpur to working on Wall Street, Aaditya’s journey reinforced one belief: founders who let emotions dictate decisions often damage their companies. Mental strength, he believes, is as critical as intelligence or capital.

Spotting the Cracks in India’s Retail Investing Boom

The idea for Multibagg AI emerged from a structural shift Aaditya observed after COVID. India’s retail investor base surged, from about 2 crore investors pre-pandemic to nearly 12–13 crore today, with SEBI projecting the number could touch 25 crore by 2030.

Despite this explosive growth, Aaditya noticed a worrying pattern. Indian investors, traditionally focused on gold, real estate, and fixed deposits, were entering equity markets without the tools or frameworks needed to make informed decisions. While institutions relied on deep research, data models, and discipline, retail investors were often guided by tips, influencers, or sheer hope.

Even highly educated professionals, he recalls, were making random, non–data-backed decisions. That widening gap between institutional intelligence and retail access became the foundation of Multibagg AI.

Why Retail Investors Deserve Institutional-Grade Intelligence

Having spent over seven years at American Express and Goldman Sachs, Aaditya had firsthand experience of how institutions operate. Every decision was backed by data, risk models, backtesting, and process. Institutions don’t gamble, they calculate.

Retail investors, by contrast, often behave as if they’re buying lottery tickets. Aaditya is quick to clarify that the problem isn’t intelligence—it’s access and time. People want to invest responsibly, but without the right tools, shortcuts take over.

Multibagg AI was built to bridge that gap, bringing institutional-grade thinking to everyday investors without overwhelming them.

Iris: The AI That Learns the Investor

At the core of Multibagg AI is Iris, an AI-powered conversational agent designed to function like a hyper-personalized research assistant. While current regulations don’t allow AI chatbots to act as Registered Investment Advisors, Iris is built to answer nearly every question investors typically ask professionals.

From company screening and portfolio analysis to concall insights, investor presentations, news interpretation, and risk exposure, Iris evolves with every interaction. Over time, it builds memory, understands risk appetite, and adapts responses accordingly.

The ambition is simple yet bold: every investing question, answered intelligently, in one place.

Walking into Shark Tank India with a Clear Mission

When Aaditya walked onto the Shark Tank India Season 5 stage, his message was unambiguous. Retail investors deserve the same quality of tools that institutions use. And human behavior is shifting, people won’t rely on static dashboards forever. The future lies in asking questions and receiving intelligent answers.

Multibagg AI, he explained, is built for that future.

The Deal That Validated the Vision

That clarity led to one of the most competitive pitches of the season. In Shark tank Season 5 , Aaditya secured a deal from Aman Gupta, Co-founder of boAt, after triggering a bidding war among the Sharks.

Originally seeking ₹50 lakh for 2% equity, Aaditya closed the deal at ₹50 lakh for 1% equity, implying a ₹50 crore valuation—double the valuation suggested in his initial ask. The Sharks were drawn not just by the numbers, but by the depth of the product and the founder behind it.

An IIT Kanpur alumnus and Super 30 graduate, Aaditya pitched Iris as an AI-native stock research platform designed to democratize institutional-grade analytics. The deal came shortly after Multibagg AI raised a pre-seed round led by AJVC, reinforcing confidence in the company’s momentum.

Shark Tank, Aaditya notes, didn’t create Multibagg AI, it amplified a vision that was already in motion.

Calm Under Pressure

Despite the high-stakes setting, Aaditya felt pressure only during the opening minute of his pitch, the segment designed for mass television audiences. Beyond that, he was firmly in his comfort zone. Explaining finance, AI, and systems came naturally, and the absence of theatrics worked in his favor.

Goldman Sachs DNA in Multibagg AI

Years spent managing balance sheets worth $1.3 trillion left a lasting imprint on Aaditya’s thinking. His exposure to asset-liability management, interest rates, risk, and portfolio construction directly shaped Multibagg AI’s architecture.

The platform enables retail investors to see what institutions see, sector exposure, diversification, forecasting, promoter activity, and risk metrics—presented in an intuitive, accessible format.

Depth Without Complexity

One of Multibagg AI’s biggest strengths is its simplicity. Aaditya attributes this to constant engagement with real users. With over 35,000 LinkedIn followers, he actively listens to investor concerns and feeds those insights back into product development.

The result is a platform that feels approachable, despite the depth of intelligence working behind the scenes.

Shark Tank’s Overnight Impact

The post-Shark Tank response was immediate and dramatic. Within a week, Multibagg AI recorded 1.25 lakh visitors, 22,000 sign-ups, and 8,000 app installs. Thousands converted into paid subscriptions, and Iris answered over 25,000 questions in seven days.

What might have taken a year happened in a week.

Building Trust in an AI-Led World

Aware of skepticism around AI-driven decision-making, Aaditya emphasizes strong guardrails. Multibagg AI does not offer buy-sell recommendations. The system is agentic, AI writes, verifies, and moderates, but humans remain in the loop.

Trust, he believes, is the real moat.

The Road Ahead

Over the next three years, Aaditya aims to onboard one crore users. His vision is straightforward: whenever Indians think about stocks or portfolios, they should open Iris.

By compressing decision-making time from days to minutes, Multibagg AI hopes to help investors act with clarity, conviction, and confidence.

Advice for Founders from Small Towns

Aaditya’s advice is grounded and unsentimental. Work hard, stabilize your finances, and don’t rush. There is no deadline, he insists. Building a company is one of the hardest things one can do, demanding emotional strength, patience, and resilience.

Only after building that foundation, he believes, should founders step into the startup world, ready to endure, adapt, and grow.

Interview Conducted by Arushi Agarwal