What happens if you fail with everyone's money?

Abhishek Bansal never let himself ask and he thinks that's the only reason Shadowfax exists.
He's the first public-company CEO on Unstarted: a middle-class kid from Meerut who quit his job without telling his parents, asked a VC for $5 million with zero orders, and was the only one still standing after the year every competitor died.
In this conversation with Avnish Bajaj, they attempt to answer:

1. Should you have a co-founder and how do you actually pick one? 
2. What should founders look for in a VC when there are multiple offers? 3. How do you tell your team you're failing?
4. Sustainable growth, or aggressive scaling?

By the end, you understand his test: accept the failure, name the core problem, tell your team. Because teams don't break on failure — they break on how you behave in it.

Chapters

0:00 Intro: our first public company CEO
1:19 Meerut, a middle-class home, and IIT Delhi
4:04 Parents didn't know he had quit his job
7:50 Q: How do you choose between VC offers?
8:47 Why he wanted a co-founder, not a skills match
11:03 Why not bootstrap?
11:28 Asking for $5 million with no product
12:23 The ₹8 lakh phone call
13:28 The angels who never sold: 1000x and counting
14:31 Three offers: $2M, $5M, $9M
17:19 Q: How do founders bounce back from failure?
17:46 The 2015 crash: five funded, one survivor
23:07 Knowing the core problem is the hardest problem
28:07 The offsite: profitable in three months
28:32 The retention numbers behind the culture
29:20 Q: Aggressive scaling or sustainable growth?
29:56 "In India, no idea is unique"
32:14 The guardrails: unit economics and 50-30-20
37:26 The CAPEX model that ran 100 iterations
39:07 When the HR team built its own hiring tool
40:20 Closing: teams compound, individuals don't

Most people assume serious AI silicon can only be built by a giant, in the cloud, burning hundreds of millions of dollars. Ravi Annavajhala did the opposite. Kinara built two AI chips for under $50M, 90% of it out of Hyderabad, and sold to NXP, one of the world's largest semiconductor companies for $307M,  all cash. It's one of the largest deep tech exits India has seen, and one of the least talked about.

In this episode, Vikram Vaidyanathan sits down with Ravi to take apart how it actually happened, and what it says about where AI is heading next.

You'll hear: 
1. Why the disruption playbook that minted the NAND-flash exits is the same one that explains Kinara's sale to NXP 
2. The clearest plain-language explanation of training vs. inference you'll find, and why inference is moving off the cloud and onto the edge
3. The four reasons edge beats cloud: cost, latency, privacy, reliability 
4. How you actually shrink a frontier model to run on a chip: distillation, compression, purpose-built retraining 
5. Why India's real AI edge isn't talent or capital, but the industrial data sitting in its factories — and why it can't afford to become a "data colony" 
6. Ravi's distinction between frugal and cheap, and why low cost has stopped meaning low capability

▶ If you're building, investing in, or just tracking India's deep tech story, this is the episode to watch.

About Intelligent Indians Intelligent Indians is Z47's thesis podcast on the people building India's technology future, for builders, operators, and investors who want the operator's view, not the press-release version.
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Chapters 

0:00 A $307M deep-tech exit you didn't hear about
0:45 Meet Ravi Annavajhala & the Kinara story
3:10 The NAND flash lesson: how startups cash in on disruption
5:45 2015: betting on edge AI while everyone chased the data center
7:00 CoreViz → Deep Vision → Kinara: the naming journey
9:15 Why 90% was built in Hyderabad — a talent bet, not a cost cut
11:30 Two chips under $50M: engineering for capital efficiency
15:20 What "the edge" actually is: training vs inference
18:00 Why edge beats cloud: latency, cost, privacy & reliability
22:45 Physical AI: robots, self-driving & the real bottlenecks
28:30 Advice to VCs: conviction, local demand & the infra gap
31:20 Frugal vs cheap: why low cost ≠ low capability
33:30 Closing: India on the cusp of the edge-AI wave

How much money is enough to make starting up safe? Vivek Sinha thought he knew: ₹50 lakh in the bank. The day he hit it, he quit.
Vivek is the founder of Emversity, which trains people for the jobs India actually has in healthcare, hospitality, EPC and manufacturing. 

Homeschooled till eight in a Bihar village surrounded by three rivers, he built Buildzar, lost ₹50 lakh, and spent nine years compounding skills at Mobikwik, OYO and Unacademy before starting again in a sector everyone had written off.

In this episode, Avnish and Vivek take on, 

1. Where did you get the confidence to do this?
2. Why didn't it work? What did you think going in that didn't play out?
3. Should I drop out and work full time on my startup?" 
4. How do I find the right co-founder?
5. How can we secure investment in a stigmatized sector despite proven traction?"
6. What stays with you: build it for the right reasons 

Chapters 

00:00 Introduction
02:00 Flood village to NIT: growing up in Bihar
06:00 First startup & why it failed: market timing
11:00 MobiKwik: 0 to 20 lakh merchants in 6 months
16:00 OYO & Unacademy: the lessons that compounded
22:00 The 9-year gap: how he killed bad ideas early
28:00 Should you drop out of college?
34:00 How many co-founders — and going solo
40:00 Building in a stigmatised, out-of-favour sector
48:00 What Mversity does + closing advice

What do you do when you've built the technology first and the first customer who tries it tells you it's not working at all?

Prashant Warrier is the first PhD and the first scientist on Unstarted. A steel-town kid from Bhilai who went from IIT Delhi to a PhD in AI, he came back to India because of a stolen passport — and built Qure.ai, whose AI reads chest X-rays for TB and lung cancer across the world.

In this episode, Avnish and Prashant attempt to answer:

 1. How do you identify a unique problem is it about passion or market cap?

2. How do you know the technology is actually working?

 3. How can founders assess whether they're early, late, or correctly timed for a market?

 4. Will frontier AI kill vertical businesses or is there domain-specific stuff left to build?

 5. Why build a cutting-edge AI company from Mumbai?

This episode is in partnership with TEAM — Tech Entrepreneurs Association of Mumbai.

Chapters 

00:00 Introduction
1:41 Steel town to IIT to a PhD in AI
3:20 SAP, and the stolen passport that sent him home
6:32 Freedom over the US visa rat race
8:17 The 2012 breakthrough that started the company
11:43 A research lab with no business plan
13:33 "A solution looking for a problem"
16:52 The reality check & the real bottleneck
19:20 TB screening: 4 weeks to 30 seconds
21:43 Detecting lung cancer early with AI
24:23 Moats, ChatGPT & the future of AI in healthcare
32:04 Why Mumbai, and advice to founders

He built a ₹100 crore brand from scratch in two years. His company rated him 2 on 5. So the question stopped being am I good at this? and became am I even the right kind of person for it?

Shashank Mehta is the founder of The Whole Truth, one of the best consumer brands built in India in the last decade. We backed him early, off the strength of a blog whose readers became the company's first customers.

In this conversation:
 
1. What do you do when you build something from zero and still get rated below the person who grew an existing brand by 5%?
2. How do you tell the difference between being bad at a job and being the wrong category of human for it?
 3. Is it risk that stops you from leaving — or is it fear wearing risk's clothes?
 4. Why does writing your worst fear down on paper shrink it?
 5. Can a single founder build a company that outlasts the founders who have co-founders?

A conversation about self-knowledge as the real moat — and why the fear that freezes you is almost always smaller on paper than the life on the other side of it.

Chapters 

0:00 Welcome & introducing Shashank Mehta
3:00 Middle class Delhi, mom's tears and the pressure to study
8:00 HUL, the startup bug & discovering he's a creator
14:00 First leap — joining Fasos, failing and coming back
20:00 The blog, the rage and the protein bar made at home
27:00 Risk vs fear — writing down what actually scared him
33:00 The 2/5 rating that built a ₹100 crore brand
38:00 Co-founders — why chemistry beats skill every time
43:00 Brand first vs revenue first — the 20 year argument
47:00 Building culture on trust and inspiration not fear and greed

Nirja Bhatt looks intimidating on paper: Columbia, Harvard Business School, strategy consulting. But she calls herself "a duck in water” i.e you never see what’s moving beneath the surface. It took her two years of analysis paralysis, ten abandoned ideas, and learning to normalize embarrassment before she could finally start.

Nirja is the founder of Laani, a pre-launch personal care brand for women, built around the categories nobody talks about. In this episode, she and Avnish go back to the very beginning.

They get into: 

1. How do you start when you have ideas but no capital? 
2. Why validate a problem, not an idea? 
3. How do you make peace with betting your own savings on yourself? 
4. Should you raise money before you have a product? 
5. And what actually separates the founders who make it?
6. An honest conversation about the part of the founder journey nobody photographs.

Chapters

00:00 Intro: Meet Neerja Bhatt, founder of Laani
01:30 Growing up in Baroda, raised by grandparents
03:00 Rejected by every dream school: the USC detour
04:30 How a professor's letter got her into Columbia
07:30 Q1: How do I start with no capital and too many ideas?
08:30 Analysis paralysis: 10 ideas and the HBS trap
11:00 Moving back to India: the waste management chapter
16:30 Q2: Passion vs. market gap — how to pick your problem
19:00 Talking to 200 women: customer validation done right
21:00 Q3 (Gubbachi founders): Hero products vs. commodity staples
26:30 To raise or not to raise: funding pre-launch
29:00 Final advice: persistence and eating a lot of shit
30:00 Outro

Chakradhar Gade had the résumé everyone's supposed to want: engineering, CFA, a hedge fund, and felt like he'd lost himself inside it. So he walked away to sell milk.

This is the story of how a finance guy who once mapped "the IRR of a cow" learned that the spreadsheet was a lie, lost all his money proving it, and rebuilt Country Delight from first principles, one customer relationship at a time.
Avnish Bajaj and Chakradhar get into the questions most founders sit with alone: 

 1. What do you do when a successful career leaves you with "a huge loss of identity"? 
2. Should you bootstrap and survive, or raise aggressively and run? 
3. How long does it really take to learn a business you've never been in? 
4. How do you tell real customer love apart from people just being nice to you?
 5. When the model that "looked very beautiful in Excel" collapses, what replaces it?

A conversation about chasing meaning over status, why bootstrapping bought six years of depth, and why, in Chakri's words, "there's no downside" to starting.

Chapters 

0:00 Welcome & introducing Chakradhar Gade
1:35 Growing up in Guntur, Infosys & chasing meaning
4:43 From MBA to Wall Street — why he chose finance
7:33 The decision to quit New York and become a doodhwala
12:05 The IRR of a cow (and why Excel lied)
14:51 Bootstrap or raise? The real answer
17:00 Raising from friends & family without ruining relationships
21:02 From ₹80 lakhs to ₹200 crores a month
23:01 The milkman model & month 60 retention
32:34 Final advice: take more risks, there is no downside

Are entrepreneurs born or made? Asish Mohapatra is certain it's the second and he'll tell you plainly he's good at maybe 3 of the 10 things a founder needs.

Asish is the co-founder of OfBusiness and Oxyzo, which he built into one of India's largest B2B commerce and lending businesses. But this conversation with Avnish isn't about the scale, it's about the intellectual honesty underneath it.

In this episode, they get into:

1. How did you get comfortable in your own skin? Was there a trigger?

2. Are entrepreneurs born or made, and how do you decide which skills to build vs. buy?

3. How do you pick a co-founder (and run a company with your spouse)?

4. Why would you never hire someone at their last salary?

5. Do you have to go public and when?

6. A conversation about failing early, being honest about it, and finding the 

🎧 New episodes of Unstarted every Thursday. For founders. By founders.

Chapters

00:00 Cold open
01:30 The boss he fired, the mentor he kept
03:30 The 10% you keep for life
07:30 Are founders born or made?
08:30 Why I got comfortable failing
08:45 Build it or buy it?
15:30 Picking a co-founder (and a wife)
19:00 Why I work 20-hour days
19:35 Baby is six days older than the company
22:45 The vulnerabilities he leads with
28:00 Never hire at their last salary
30:30 Always the next IPO?
35:00 Be yourself. Keep building your superpower.

Can you be a founder without ever founding anything?

Amarjeet Batra has spent 25 years building other people's companies, first Baazee, eBay, OLX, and now Spotify India, and never once thought of himself as an employee. He's what Avnish calls "professionally unstarted": a founder from within.

Avnish and Amarjeet get into the questions most operators never say out loud:  

1. If you have the skills, the confidence, and the network, but not the one big idea, what do you actually do with that? 

2. Is raising a fund a solution, or a responsibility you take on before you've found the problem?

3. Why would you choose 1% of a billion-dollar company over 100% of a ten-million-dollar one? 

4. How do you build a category when ten players already exist and you've arrived last? 

5. When is a difficult problem worth solving, and when does the market simply not care enough to pay?

6. This is a conversation about range over specialisation, ownership without a cap table, and why some of the most entrepreneurial people you'll meet never start a company of their own.

Chapters

00:00  Cold open
01:30 The professionally unstarted founder
02:55 Baazi, the born-again moment
05:10 Why I broke every rule of specialization
08:30 The eBay epiphany: time to do something bigger
09:43 China, and the scale that humbled me
18:26 The power of moving last
20:05  Building the category nobody built
21:15 Is there still a marketplace to win?
22:56 Disruption, distribution, and the AI shift
23:58  Q: How do you actually scale an events business?
26:15 Q: (cont.) Why your event might be the wrong product
28:14 Q: Should we build a place to apprentice under founders?
31:32 How to actually reach a busy operator
34:20 Q: Difficult problem, or one nobody will pay for?
35:09 Problem-first, and the willingness-to-pay test
36:37 Vitamin or painkiller
39:01 Play-front music: a business model flips
41:09 Why success looks overnight

What does it actually take to build AI for 70 crore users?

Vikram sits down with Rahul Chowdhury -  co-founder and CTO of PhonePeto talk about how India's most scaled fintech is approaching AI. Not with hype or a top-down mandate, but with a quiet, deliberate, engineering-first philosophy that started four years ago with a small team focused on making developers happier.

Rahul shares the inside story of PhonePe's AI journey from building their own LLM gateway and Agent Hub, to launching AI search with Microsoft, to betting on on-device models for privacy and cost. And it ends with the biggest idea of all: India's DPI stack has spent a decade making data AI-ready. 

The opportunity now is to use it to build the bank branch of one — truly personalized financial products for every Indian.

If you're a founder, engineer, or product leader trying to understand where India's AI story is really headed, don't miss this.

What you'll learn

🔹 Why PhonePe avoided output metrics in year one of AI and why it worked

🔹 How to build an AI culture without a top-down mandate

🔹 What an LLM gateway is and why every scaled company needs one

🔹 Why on-device models are the right bet for consumer AI in India

🔹 How DPDP will reshape how companies think about AI and data

🔹 Why India's role in global AI is in applied AI — not foundational models

🔹 How DPI × AI creates the opportunity for hyper-personalized financial products

Chapters

0:00 Intro & who is Rahul Chowdhury
02:30 PhonePe's AI journey: tinkerers to transformers
06:00 The DevX team: why developer happiness came first
10:00 Don't rush into AI — the engineering first mindset
14:30 Building the LLM gateway & data stack
18:00 Agent Hub: PhonePe's internal marketplace of agents
22:00 AI Search with Microsoft & on-device models
26:00 Why India needs edge models, not foundational ones
30:00 DPI × AI: the bank branch of one
34:00 Conclusion