Anjali Sardana grew up in northern Virginia, studied biology at Georgetown, worked at Bain Capital — and then, without telling her parents, flew to India and founded Pronto: a platform building the world's largest labor organization network, starting with home services.

In this episode of Unstarted, Anjali breaks down how she picked an operations business over a product business (and why), why she sees India's informal labor market as a trillion-dollar opportunity, and the founder mindset that got her through the messy, chaotic, sleep-deprived early days.

She also gets brutally honest about faking confidence, hiring missionaries not mercenaries, and why she thinks most human limitations are completely made up.

Chapters

0:00 Intro — Meet Anjali Sardana
1:20 Growing up in Virginia, studying biology at Georgetown
3:10 The evolution framework that shaped her business thinking
5:00 Product vs. operations vs. distribution — how she chose
8:30 Why India? The labor-market thesis
12:00 Moving to India with zero experience — and hiding it from her parents
15:40 Fake it till you make it: raising a seed round at Bain Capital
19:15 Running pilots, vibe-coding the app, and getting the first bookings
24:00 The Kapil story — recruiting 30 workers in one afternoon
28:00 Operating 24/7 with 5 people, sleeping in shifts
31:30 Building culture: missionaries vs. mercenaries
36:00 Urgency as a core value — actions beget information
39:30 Conviction vs. market signals — how to balance both

India's GPU footprint is on track to grow 40x by 2030, from ~50,000 today to a couple of million. 

That number is bigger than any public forecast. Sharad Sanghi has the unusual standing to make it: he built Netmagic into India's most significant datacenter business, and he's now running Neysa, the only neo cloud in India that Semi Analysis has rated, backed by Blackstone.
In this episode of Intelligent Indians, Rajinder Balaraman and Sharad cover:

1. Why neo clouds exist as a category, and what hyperscalers structurally can't do for one market 

2. The ITQ case study: how to define ROI before infrastructure 

3. The three infra mistakes that quietly cost AI teams 10x their compute spend 

4. Why power, not GPUs, is the real bottleneck, and why 50% of India's data centre capacity sits in one city 

5. What  India's AI Mission could actually unlock in the next phase

If you're building AI infrastructure in India, tracking the space as an investor, or working on policy in the area, this is the operator view. 

From someone whose entire balance sheet depends on getting the call right.

Chapters 

00:00 India's AI Moment The Big Picture
02:00 Welcome Introducing Sharath of Neysa
03:30 How He Built India's First Data Centre with NetMagic
06:00 How ChatGPT Sparked the Idea for Neysa
18:00 India is 2nd Largest AI Consumer 
21:00 50,000 GPUs Today. 2 Million by 2028 
24:30 Neysa vs AWS, GCP, Azure 
28:00 Why Indian Banks Are Early AI Adopters
31:30 Financial Services, Healthcare, Manufacturing 
35:00 PhonePe, Perfios, Hungama - Real AI Use Cases in India
38:30 Why Most AI Projects Stay in Pilot and Never Reach Production
52:30 GPU Obsolescence Risk — How Neysa Manages It
55:00 Healthcare, Education, Agriculture — Where Founders Should Build
58:30 IIT Bombay and the Bharat Gyan Project
1:01:00 Why India Needs to Keep Its AI Talent at Home
1:04:00 Why He Refused to Flip the Company Outside India
1:06:30 What It Takes to Make India the AI Research Capital of the World

Chirag Taneja built GoKwik into 1 in 5 D2C checkouts in India. But the path there was a series of bets that didn't work, jobs that didn't last, and one moment in 2020 where the suitcases for Canada were packed and waiting in his living room.
In Episode 12 of Unstarted, Chirag sits down with Avnish Bajaj to talk about what it actually means to keep tinkering, and when tinkering becomes the thing that holds you back.
They get into: 

1. What's really important to start a business: idea, capital, or knowledge? 
2. Why choosing the right problem matters more than solving any problem 
3. The Canada PR that almost happened (and the suitcases that are still in his house) 
4. Probabilistic thinking, and why "generate choices" beats "make decisions" 
5. Should you have a co-founder you don't already know? 
6. How he thinks about ESOPs, the size of the pie

Unstarted is a Z47 series. For founders, by founders. New episode every Thursday.

Chapters 

00:18 From the shop floor to a 1-in-5 D2C company
01:35 A banker father, a single parent, and "play with intent"
03:15 Why he chose Delhi College over IIT Delhi Civil
05:30 The first Asian team to build a Formula race car
06:25 The Maruti bet that landed him on the shop floor
07:10 Q: Idea, capital, or knowledge — what matters most?
08:50 How Bombay Shaving Company became the foundation of GoKwik
09:35 The right problem matters more than the right solution
10:55 Payments were broken in 2005. They were still broken in 2017.
11:50 Pick your game: badminton or golf?
13:20 The Canada PR, the suitcases, and the trip that never happened
15:25 Generate choices before you make decisions
17:50 When the tinkerer turns on himself
19:15 Why "what worked then" stops working at 1-to-10
22:45 Q: When should you have a co-founder?
24:45 Why arranged co-founders are too risky
28:30 Closing

Most founders can't tell you the moment they decided to build. Vedang Patel can. He was 23, a finance analyst with IIM seats in hand, and he looked at the MBA-holder sitting next to him in office and asked himself one question: "Is that what I want to do?"

The resounding no from every section of his brain, and the ₹5.25 lakh he and his co-founders had between them is what became The Souled Store. ₹1000 crore in revenue, 

₹150–200 crore in profit, an NSE bell on the way.

In this episode, Avnish and Vedang sit with three questions sent in by aspiring founders:

1. How do you actually validate an idea?
2. How do you separate polite encouragement from real market demand?
Brand or revenue first?
3. They also talk about the part most founders won't: the $10 million Vedang got "lost in frameworks" with, the 15-20 CR in personal-guarantee debt, and how exponential's cheque pulled him back.

Chapters 

00:00 Cold open
01:30 From a cupboard of t-shirts to ₹1000 crore
03:30 The Sunday-Monday test
06:30 "She cried for days"
08:30 Risk vs Recklessness
11:00 Q: How do I validate my idea?
13:30 ₹5.25 lakh, no money for movies
15:30 Discounted PMF is false PMF
17:00 Q: Polite encouragement or real demand?
20:30 The empty chair of the customer
24:30 When the $10 million came in
27:30 "Maybe I should be inspired by Neera Modi"
30:30 Q: Brand or revenue first?
32:00 A brand is what the customer expects
35:30 Why he never left Bombay
38:30 The ESOP wall and the 5-10-85 rule
41:30 "Don't overthink. Start."

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India's AI moment is louder than its rank. 100M+ ChatGPT users. #2 globally in usage. Still 76th in the world on per capita penetration. So what's actually happening on the ground?

In this episode of Z47 Moments, Vikram Vaidyanathan and Ashwin Raguraman (Head of AI, walk through The India AI Edge: a three-month primary research effort by Z47, OpenAI, and Zinnov. The report draws on first-party ChatGPT data from OpenAI and interviews with 100+ CXOs across India's largest enterprises, traditional businesses, and emerging companies.

They unpack:

To read the full report, go to:

The India AI Edge Website: https://z47.com/how-india-uses-ai
Link to report: https://www.ai-edge.z47.com/The-India-AI-Report.pdf

Chapters

00:00 — Cold Open: The Stats That Set the Frame
00:49 — Inside the Report: 100M Users, 100+ CXOs, OpenAI Data
02:14 — How AI Is Redrawing India's Map
04:59 — The Gen Z Takeover
11:24 — Work to Non-Work: India's Usage Flip
15:01 — Enterprise AI: The Four Archetypes
25:27 — The Enforcer Trap (And How to Escape It)
33:21 — Can AI Close India's Trillion-Dollar Gap?
37:22 — Compute, Talent, Data, Companies: The Four Pillars
47:15 — India's AI Ecosystem & Closing

What do you do when the resume is perfect but the work isn't yours yet?
Utkarsh Gupta grew up in the Dainik Jagran family in Kanpur, a thirty-person joint family, a media legacy, and a grandfather who once left an entire newspaper page blank during the Emergency and went to jail for it. 

By thirty-two, Utkarsh had built his own answer: Comet, the Indian sneaker brand that put a mango shoe and a rubber-ducky shoe into the world before it ever touched a marketplace.

In this episode, Avnish Bajaj and Utkarsh sit with the questions most founders never say out loud:

Was the MBA real, or was I procrastinating? 

1. How do you build your own legacy when one's already been handed to you? 

2. How do you tell persistence apart from stubbornness when the first launch sells two pairs? 

3. When everyone says list on Myntra, why wait two and a half years?

A masterclass in brand building, told as a confession.

Chapters

0:00 Introduction
0:50 Growing up in Kanpur's joint family
1:13 How Dainik Jagran started on a cycle in 1940
2:09 Why he left a media dynasty to build his own thing
4:47 Doon School changed everything at age 11
6:20 Grandfather's lesson: don't be afraid to scale
11:50 How Chicago's sneaker culture sparked Comet
13:31 Creating your own surface area of luck
14:55 Finding co-founder Dushyant
23:24 The 4-pillar brand strategy that built Comet
27:09 Why they waited 2.5 years before joining Myntra
28:55 The Mango shoe sold 2 units in 4 days — they persisted anyway
31:40 3 metrics every founder should track
41:46 Building the sole from scratch (4-5 moulds, 6 months)
43:02 Creasing problem: sourced a secret material from Korea
46:12 Instagram → Stores → Myntra: the distribution sequence
49:43 Exclusive reveal: the Rubber Ducky drop (May)

Do you need an original idea to start a company? Do you need to be a consumer of your category? Do you need the "right" co-founders?
Manish Taneja was none of those things. He grew up in Faridabad a self-described "frog of his own well." He went to IIT and "felt very small." He became a banker, then an investor, then started a beauty company with two other male engineers, with no female co-founder, and no personal stake in the category. He still built Purplle into one of India's largest beauty platforms.
In this episode of Unstarted, Avnish Bajaj and Manish sit down to work through the questions that every founder without a clear edge asks themselves:

1. Do you need an original idea, or is it okay to be a "copycat entrepreneur"?  When VCs tell you your team is missing something 

2. Do you fix the weakness or back your strength? – How do you find a wedge in a category where everyone else has more money, more experience, and more insider knowledge? 

3. What do you do when your ego won't let you leave — and is that the thing keeping you in the game? 

4. How do you build responsibly without losing your edge?

Manish's answer to all of it, in the end, comes down to two lines: back your strengths, and build responsibly. This conversation is about how he got there.

Chapters

00:00 The $100 million mistake
01:55 Faridabad, the frog in the well
03:03 Feeling small at IIT, and the speech that changed everything
05:31 Lehman, Avendus, and the long apprenticeship
08:52 "I was the original copycat entrepreneur"
12:58 The feedback from Matrix: no woman co-founder
14:54 Why beauty, and why now
17:52 Dabau early: the rosemary water playbook
22:00 How Purplle won Kerala (and met the priests)
26:02 The internal compass, and saying no to Thrasios
28:53 Why your ego won't let you leave
30:36 Why he built in Bombay
33:17 The IPO question
35:49 Build responsibly

What do you do with the regret of being right too early?

Aakrit Vaish started Haptik in 2013: an AI chatbot company nine years before ChatGPT. By 2016 he knew the market wasn't ready. He kept going anyway. In 2019 he sold to Reliance Jio. In November 2022, he watched the world finally catch up to the thesis he'd carried for a decade and for a few weeks, sat with the sentence: "This should have been me."

Today he's co-founder of Activate, an AI-native VC firm running with two partners, one employee and seven agents, and an advisor on the India AI Mission. In this episode, Avnish Bajaj sits down with a founder who has rejected him more than once, and asks the questions most founders quietly carry:

1. How do you know whether you're early, late, or correctly timed?
2. Why do you keep going when the rational move is to stop?
3. When the world eventually proves you right, what do you do with the grief?
4. In AI today, what does it actually mean to be in the 99th percentile — globally, not locally?
5. How does a high-agency founder stay ahead when the tools keep rewriting the job?
6. What Aakrit lands on: market timing matters, but identity matters more. 
7. Mission over everything else. And the only advice he gives, seven times a day, to anyone who'll listen: have agency. Build. Don't wait.

Chapters

00:00 Why Did You Let ChatGPT Happen?
02:30 Welcome to Unstarted — Introducing Aakrit Vaish
04:00 Growing Up in Juhu — Normal Mumbai Business Family
06:30 UIUC, PayPal Mafia & Moving to Silicon Valley
09:00 Why He Came Back to India at 27
11:00 What Was Haptic? India's First AI Chatbot Company
14:00 The Alexa Moment That Started It All (London 2012)
18:00 How Founders Can Know If They Are Too Early or Too Late
23:00 2016 — He Knew It Was Too Early. He Kept Going Anyway
27:30 Fear of Failure vs Fear of Not Trying Hard Enough
31:00 The Pull vs Push Test — The Clearest PMF Signal
35:00 Why He Sold Haptic to Reliance
38:30 ChatGPT Launched. His First Reaction Was Personal
43:00 "Should That Have Been Me?" — The Honest Answer
47:00 From Reliance to India AI Mission to Activate VC
51:00 How to Know Which Problem Is Worth Solving With AI
55:30 99th Percentile or Nothing — The New Bar for AI Founders
59:00 Why AI in India Is the Most Ignored Opportunity
1:03:00 Anthropic vs OpenAI — Two Different Strategies Explained
1:07:00 Voice AI, FinTech & How GDP Will Actually Grow
1:11:00  The K-Shift — GDP Growth at the Cost of Inequality

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What happens when you spend 13 years building something, and for most of those years, the people around you think it's not going to work out?
Jaydeep Barman left a gilded career at McKinsey's London office to bet on a single roll shop in Pune. What followed was a decade-plus journey through India's costliest real estate market, the invention of an entirely new category (cloud kitchens — before anyone called it that), and the slow, painful work of staying in the game while companies that started years after him became unicorns overnight.

In this conversation, Avnish and Jaydeep wrestle with:

1. How do you find the one insight nobody else has, and trust it when the world disagrees?

2. What do you do when your investors mentally write you off?

3. Why does every real innovation at Rebel come from the moments they were closest to shutting down?

4. How do you build a team that stays for 13 years, through the pain, the doubt, and the long wait?

5. This is a conversation about what it actually costs to stay in the arena longer than everyone expects you to, and what that buys you that nothing else can.

Chapters: 

00:00 The reality of startup comparison & investor pressure
01:30 Why we didn’t pivot to food delivery (despite the hype)
02:30 From McKinsey to starting a food business
04:10 The first roll shop: how Fasos began
09:00 Learning the business & why curiosity matters most
11:20 Insight v/s timing: finding your “right to win”
13:40 Building a cloud kitchen breakthrough
17:30 Founder mentality vs CV mentality
20:00 Hiring, ownership & building real culture
24:50 Performance vs culture: who stays, who leaves
27:20 Rock bottom moments: running out of money & pushing through

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What does it take to fix the most broken system in America — from the outside?

Ajay and Aniket, co-founders of Coral AI, had zero healthcare experience when they started. What they had was a burning problem, a one-way plane ticket to the US, and a relentless drive to understand healthcare from the ground up — visiting 17 cities in 30 days, becoming interns, and reading thousands of faxes doctors still send in 2026.

In this episode of Zee47 Moments, Ashwin and Vikram sit down with the founders to unpack how Coral is using AI to eliminate the administrative chaos of patient referrals — cutting weeks of back-and-forth down to minutes — and how they're building one of the most AI-native companies in healthcare.

🔍 What we cover:

• Why 40% of primary care visits result in a referral — and how that process is broken
• How fax machines still run US healthcare in 2026
• The technology behind going from 80% to 99.1% accuracy on medical documents
• Why Epic and OpenAI can't solve this problem — but Coral can
• Winning head-to-head against a competitor that raised $100M+
• The "forward deployed engineer" model and why it's not services
• Building a lean, 10x team of future founders

Coral just raised $12.5M led by Zee47. This is their story.

─────────────────────────────
CHAPTERS

0:00 17 days to get a scan
2:22 Picking healthcare with zero healthcare background
4:48 17 cities in 30 days and the Mamba mentality
8:26 Inside the fax machine: how a US referral actually works
14:16 Getting to 99% accuracy (and why 95% isn't enough)
20:48 Beating a competitor with 10x the money
24:56 $100K to $500K without a sales team
28:07 The 10X-only team and the FTE model done right
33:40 Failure, rapid fire, and what's next

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