May 2026 – Kae Capital

How to Build for Bharat

Posted on May 29, 2026May 29, 2026 by Kae Team

Most founders building “for India” are building for 10 cities.

That’s fine. Bengaluru, Mumbai, Delhi, Hyderabad, Pune, Chennai, and the other metros are real, high-GDP, high-density markets. But they are not Bharat. And Bharat, India’s Tier 2, Tier 3, and district-level economy, is where the next generation of category-defining companies will be built.

The challenge: almost all the advice circulating about building for Bharat is wrong, borrowed from consumer internet frameworks, or written by people who have never sold to a shopkeeper in Surat.

This is a practical guide. What actually works when you’re building for India beyond the metros.

The Core Mistake: Treating Bharat as a “Cheaper India”

The most common error founders make is treating Tier 2/3 India as a price-compressed version of metro India. Same product, lower price point, different geography.

This doesn’t work because Bharat is not structurally cheaper metro India. It has fundamentally different:

Trust mechanisms: Business in Bharat runs on personal relationships and community reputation, not contracts and institutional credibility.
Language: Your product may need to work in Hindi, Marathi, Tamil, Gujarati, Kannada, or Odia. English-first is a silent filter that eliminates most of your potential market.
Distribution: The last-mile infrastructure that exists in metros (logistics networks, payments rails, formal retail) is thin or absent in many Tier 3 geographies.
Decision-making cycles: A kirana owner in Nagpur doesn’t make a buying decision the way a procurement manager in a Bengaluru SaaS company does. The cycle is slower, more relational, and community-validated.

Founders who treat these as minor surface-level tweaks (translate the app, lower the price) fail. Founders who redesign the product around these structural realities often find markets an order of magnitude larger than they expected.

What the Bharat Opportunity Actually Looks Like

Before the tactical section, let’s be specific about what’s at stake.

MSMEs: India has approximately 63 million micro, small, and medium enterprises. Roughly 80% of them are outside the top 10 metros. Most are in manufacturing, trading, services, and agriculture. Most do not have a bank account actively used for business, a GST-compliant invoice process that works smoothly, or digital inventory management. Many have a WhatsApp group for procurement.

The kirana economy: India’s 12 million kirana stores serve as the primary retail infrastructure for the country. Roughly 90% are outside metros. They collectively move ₹30–40 lakh crore in goods annually. Their primary logistics partner is still the local wholesale market and the trusted supplier who visits on a fixed day.

The working capital gap: India’s formal MSME credit gap is estimated at ₹20–25 lakh crore. Most of this gap is in non-metro geographies where formal credit assessment infrastructure (bureau scores, audited financials, property documentation) doesn’t apply to the majority of business owners.

These are not “emerging” markets in the sense that they’re small today. They are the majority of Indian economic activity, operating outside the infrastructure that startups have built so far.

Five Principles for Building in Bharat

1. Trust before transaction

In metro India, a founder can sell to a business if the product works and the price is right. In Bharat, a business owner needs to trust you before they’ll try your product. That trust is earned through community, not through features.

In practice this means:

Hire from the geography. Your first sales rep in Surat should be from Surat, ideally with existing relationships in the trading community you’re targeting. A salesperson from Bengaluru who doesn’t speak Gujarati will struggle with leads that a local person converts in one meeting.

Use reference customers aggressively. In Bharat markets, one happy customer in a community can unlock 20 more through word of mouth. Your CAC is effectively zero for the second 20 customers if the first one talks. Design your onboarding to make customers feel like they want to tell others.

Be present physically, at least initially. The founders who figure out Bharat markets typically do it by spending time there: not visiting from Bengaluru, but being in Surat, Indore, Coimbatore, or Rajkot for weeks at a time. The insight you get from sitting in a wholesale market for two days is not available from any secondary research.

2. Design for spoken language, not written English

The default startup assumption is that users will read your interface. In Bharat, many business owners read slowly or not at all in English. Some read slowly in their own language. Voice-first or WhatsApp-first interfaces are not compromises. They are the right interface for this market.

Companies that got this right early:

Udaan (B2B commerce): built around a mobile-first, Hindi-compatible flow for the kirana-to-distributor transaction. Made the procurement experience feel like a WhatsApp conversation, not a B2B portal.
BharatPe (merchant payments): early success in non-metro markets specifically because onboarding was designed for merchants who had never used a smartphone for business before.
LocoNav (fleet management): built for truck fleet operators, many of whom are semi-literate. Designed alerts and notifications in local languages, used voice assistants.

Practical test: Have someone in your target geography use your product without any help. Watch what confuses them. If an English sentence is creating a 10-second pause, it’s a drop-off point. Remove it.

3. Distribution is the product in Bharat

In metro India, good products often find distribution through digital channels: app stores, Google ads, LinkedIn outreach. In Bharat, the product’s distribution model is as important as the product itself. Often more.

The most effective Bharat distribution channels:

Trade associations and industry bodies. If you’re selling to textile manufacturers in Surat, the Surat Textile Association can unlock your entire market or shut you out. Understanding the political and social structure of the trade association is as important as understanding the product-market fit.

Franchise and agent networks. Many successful Bharat businesses distribute through a network of local agents who earn commissions and handle the local relationship. The technology company becomes the platform; the agents are the distribution. This works for insurance (Digit, Acko), lending (IndiaLends, CreditBee), and increasingly for B2B commerce.

FOCO (Franchise-Owned, Company-Operated) or FOFO (Franchise-Owned, Franchise-Operated) models. For physical-world companies, owning your own outlets in Tier 2/3 markets burns capital quickly. Franchise structures transfer the local knowledge problem to people who actually have it.

The payment distribution insight: PhonePe and Paytm didn’t win in Bharat by being better apps. They won by building dense agent networks that activated merchants in person, handled disputes locally, and created a physical presence that digital-only competitors couldn’t replicate.

4. Working capital is the product

In Bharat, the business opportunity is often not the software or the logistics or the marketplace. It’s the credit.

Most Bharat business owners operate on thin working capital: they pay suppliers before they collect from buyers, they need to carry inventory for weeks, and they have limited access to formal credit when they need to expand. The company that solves their credit problem earns a relationship that is nearly impossible to displace.

Founders building in Bharat should ask: can working capital be part of our product?

B2B marketplace + embedded credit (buy inventory from us, pay in 30 days) = lower buyer acquisition cost and higher retention
SaaS for kirana + credit against verified transaction data = faster product adoption and a lending business
Logistics platform + advance payment to truckers = solved the #1 pain point for fleet operators before it’s a product at all

The account aggregator framework (launched 2022) makes business cashflow data from bank accounts shareable with consent. This data can underwrite Bharat businesses in ways that traditional credit assessment cannot. Founders who build consent-based data flows into their products early create a lending capability that is 3–4 years ahead of competitors who try to add it later.

5. Accept that your metrics will look different

Most startup advice assumes a certain metrics model: acquire users quickly, achieve high engagement, scale aggressively, raise the next round on growth rates.

Bharat businesses often look worse on these metrics initially, and better on the fundamentals that matter.

Lower NPS volatility. When you earn trust in a community, churn is very low. A kirana owner who has been using your platform for six months and trusts you doesn’t leave for a competitor who dropped their price by 5%.

Slower viral loops. Word of mouth in Bharat is slower than social media virality. But when a community adopts your product, it adopts it collectively. The adoption curve is S-shaped and steep once it tips, rather than linear.

Higher servicing costs early. The first hundred customers in a Tier 2 market will require more hand-holding than a cohort of Bengaluru SMEs. Accept this as market development investment, not as an inefficiency. The economics improve dramatically at scale.

Longer sales cycles. Bharat B2B sales cycles can be 2–3x longer than metro equivalents. This is not negotiating behavior. It’s relationship development. A founder who tries to compress this cycle by applying pressure will lose the sale.

The Geography Selection Problem

Not all Tier 2 cities are the same. There are meaningful structural differences between, say, Surat (textiles, diamond trade, dense MSME base), Coimbatore (engineering, manufacturing, strong industrial ecosystem), and Guwahati (entry point for Northeast India, different cultural context, different regulatory landscape).

Before choosing a Bharat geography to enter, understand:

What is the dominant trade / industry in this geography? Your product should have an obvious application to the local economy.
What is the existing digital infrastructure? Some Tier 2 markets have strong smartphone penetration and 4G coverage; others don’t. This affects your product assumptions.
Who are the community influencers? In every market, there are 5–10 people whose endorsement matters disproportionately. Find them before you enter.
What VC-backed company has already been here before you? If someone tried and failed in this market, understand why before you replicate their mistake.

The Founder Profile That Succeeds in Bharat

Kae’s portfolio has taught us something specific about the founder type that succeeds in Bharat markets.

They typically have personal exposure to the problem — they grew up in or near the community they’re serving, had a family member in the trade, or spent 2–3 years working in the industry before starting. They have an insider’s understanding of the informal rules that govern the market.

They are not deterred by the absence of comparable metrics. When a metro VC says “show me your DAU” and the founder says “my product is used once a week but it’s embedded in every workflow and churn is 3% annually,” the founder needs to be able to explain why that’s a better business than high-DAU with 30% annual churn. Bharat founders who internalize this can raise from the right investors and ignore the wrong ones.

They speak the language — literally. Not necessarily every language of every geography, but they have enough cultural proximity that their team is credible in the market. A founder who has to translate every customer conversation through an intermediary is at a structural disadvantage.

What Kae Looks For in Bharat-Focused Founders

We have backed companies operating in Bharat markets across commerce, manufacturing, healthtech, and logistics. What distinguishes the founders we back:

They have firsthand insight, not secondhand research. They know the market because they were inside it, not because they read a McKinsey report on India’s Tier 2 economy.

They have an early customer signal. Not necessarily revenue — but evidence that the community finds the problem interesting. A letter of intent from a trade association. A paid pilot with 10 kirana owners. A design partner conversation with a manufacturer in Coimbatore. Zero signal is hard to underwrite.

They have a specific answer to “why this geography first?” The best Bharat founders don’t start everywhere. They start in one community, one city, one industry cluster — and they own it before expanding. The ones who try to be pan-India on day one typically fail to be anywhere.

They understand the working capital dimension. Even if they’re not building a lending product, they’ve thought about how credit fits into their market. Because in Bharat, it almost always does.

A Note on Why This Matters Now

The digitization of Bharat is not a 10-year thesis. It’s a current-state transition.

For the first time, there is a generation of founders who grew up in Tier 2 and Tier 3 India, got engineering or MBA educations, worked in a metro or abroad for a few years, and came back. They understand both worlds. They know how a kirana owner in Nagpur thinks and they can write a software product spec. This cohort didn’t exist at scale in 2015. It does now.

Alongside them: UPI has already changed the trust infrastructure for payments at the base of the pyramid. A merchant in Rajkot who did zero digital transactions in 2019 now processes hundreds of UPI payments a month. That transaction history is an identity. It’s an underwriting signal. And it’s a relationship that someone is going to build a product on top of.

GST digitization has created a paper trail for MSME businesses that didn’t exist before. Roughly 15 million businesses now have a formal transaction record through GST filings. That data is the foundation for credit, inventory intelligence, and procurement optimization products that couldn’t have been built on an informal economy. The data became real in 2022. The products built on it are being built now.

And the first cycle of Bharat companies has closed the loop for investors. Porter, Zetwerk, Jumbotail, and others have proven the category exists and that Bharat businesses pay for real solutions to real problems. The investor skepticism that killed promising Bharat pitches in 2016 and 2017 is lower now. The bar to raise a seed round for a Bharat-focused company has dropped. The bar to build the actual product has not changed. That gap is the opportunity.

Frequently Asked Questions

What is “Bharat” in the Indian startup context?

Bharat refers to India beyond the major metropolitan cities: Tier 2 (cities with populations of 1–5 million), Tier 3 (smaller cities and district headquarters), and semi-urban/rural India. It represents the majority of India’s population and economic activity, but has historically been underserved by venture-backed technology companies.

Why do most startups fail to build for Bharat successfully?

The most common failure mode is applying a metro India or US product playbook to a structurally different market. Bharat requires a different distribution model, language-first product design, trust-based sales, and often an embedded working capital component. Founders who treat it as a cheap version of metro India fail; founders who redesign around Bharat’s actual structure succeed.

Does Kae Capital invest in Bharat-focused startups?

Yes. Many of Kae’s investments address markets that are structurally tied to Bharat — MSME commerce, manufacturing, B2B logistics, fintech for informal businesses. Kae specifically looks for founders with India-specific insight, which often means insight into how the non-metro economy actually works.

Is there venture capital available for Bharat-focused companies?

Yes, but it requires framing the opportunity correctly for investors. Bharat metrics look different from metro metrics: slower acquisition, lower churn, longer sales cycles. Founders need to explain why the fundamentals are stronger, not try to make Bharat metrics look like Bengaluru metrics. Kae, Blume Ventures, Stellaris, and India Quotient are among the funds with specific Bharat exposure.

What sectors work well in Bharat markets?

B2B commerce and supply chain, MSME credit and fintech, agritech, small manufacturer SaaS, logistics and fleet management, health infrastructure, and rural insurance. The common thread is that they address infrastructure gaps — the things that exist in metros but don’t exist at the same quality in smaller geographies.

Kae Capital has been the first institutional investor in India since 2012. Portfolio companies include Porter, Zetwerk, Tata 1mg, HealthKart, Myntra, and 90+ others. $7.7B+ portfolio value. Pitch at kae-capital.com.

Did You Buy That, Or Were You Sold It?

Posted on May 27, 2026May 27, 2026 by Kae Team

Most D2C founders in India can tell some version of this story. They log into Meesho on a Monday morning to find that the bestselling SKU last quarter is not the one they had been pushing ads behind. They didn’t know it was the bestseller until the dashboard told them. The algorithm had picked it up, decided it looked like the kind of thing a particular cohort of buyers would respond to, and pushed it into millions of feeds. The founder, increasingly, is a passenger on their own business.

That story is the entire shift, in one anecdote. The world is moving quickly from one where humans decide what they want and machines help them find it, to one where machines decide what we want and we cheerfully oblige. If you are building anything that ends in a transaction, this is the single most important trend to internalize this decade.

The shelf is gone

For most of commercial history, consumption had a clean architecture. There was a need (or a manufactured one), a category, a set of brands inside it, and a shelf, real or digital, where you went to compare. You walked into a Big Bazaar, or you typed “running shoes” into Amazon, or you asked a cousin. The mental motion was: I want X, who makes the best X.

That motion is dying. Watch any heavy user of Instagram, Meesho, or YouTube Shorts today. They are not searching. They are scrolling. Things appear. Some of those things get bought. The category, the comparison, the intent, all of it has been hollowed out. The feed is the shelf, the recommendation is the catalogue, and the algorithm is the salesperson who happens to know what the buyer has been doing for the last three years.

The numbers tell the same story. By Bain’s estimates, India will have 600 to 650 million short-form video consumers in 2025, with active users spending close to an hour a day inside these feeds. Globally, the strongest proof point is TikTok Shop, which is not available in India but is the most useful data point we have for where feed-driven commerce is heading. Its global GMV went from roughly $0.9B in 2021 to $33.2B in 2024 and is on track for around $66B in 2025. That is a 70x jump in four years on a platform that, by design, you cannot search the way you search Amazon. The fastest-growing surface for commerce in the world is one with no shelf at all.

This sounds like a small UX change. It is not. It is a transfer of power.

Intent is the thing being eaten

In the search world, intent was customer-side. The user knew what they wanted, and the platform helped match them to it. Google’s whole business is monetizing intent that already exists. Brands paid to be the first answer when someone walked up to the counter.

In the feed world, intent is platform-side. The platform decides what the user should want today, mostly based on what people who look statistically like them wanted yesterday. The user does not bring intent to the screen. The screen manufactures it. This is why so many of the products people now buy are ones they did not know existed twenty minutes earlier, and why nobody can remember a week later what made them click.

The implication for brand building is severe. The old playbook was about owning a piece of mental real estate, so that when intent arrived, you were the first answer. Brands spent a decade making “cola” mean Coke. But if intent itself is being generated inside an algorithm that has no memory of your TV spots, no respect for your shelf placement, and no opinion on your equity, you are not really building a brand anymore. You are training a recommender. The job has changed and most CMOs are still doing the old one.

Taste in the time of feeds

The cultural side of this is stranger than the commercial side. Algorithms were supposed to give everyone a personalized world. In practice, they have made taste both narrower and weirder at the same time.

Narrower because most feeds optimize for engagement, which is a small slice of what humans actually value. Weirder because the feedback loops compound at insane speed. A small group of people develops a niche interest, the algorithm notices, amplifies, mutates, and a few quarters later there is a multi-hundred-million-dollar brand built around something that did not exist a year earlier.

The clearest example is Stanley. The Stanley Quencher cup did $73M in 2019, $94M in 2020, $194M in 2021, $402M in 2022, and around $750M in 2023, largely on the back of TikTok virality. Nobody set out to want a $45 stainless steel cup. The want was assembled, downstream, by a feed. The same playbook is now visible in Indian D2C, where Reels-led brands in skincare, fragrance, snacks, and home goods are scaling from zero to meaningful revenue in twelve to eighteen months, without ever doing a conventional brand campaign.

The more unsettling part is what this is doing to creators, not just to consumers. Listen to almost any chart-topping song today. The hook arrives in the first few seconds. The intro is gone. The chorus is engineered to be loopable in a fifteen-second Reel. This is not an accident. It is what happens when artists, consciously or not, start writing for the algorithm instead of the song. An artist makes a good track. The algorithm picks it up. The artist (and the label) studies what worked, the cut points, the tempo, the lyric that became a meme. The next track is built backward from those signals. Other artists copy what they see working. The recommender, having learned from what it amplified, rewards more of the same. The loop closes. Art drifts downstream of distribution.

The same logic now governs Reels-led D2C. Founders A/B test thumbnails, hook lengths, and product angles not because their customers asked for any of it, but because the algorithm tells them which variant got watched to the end. The customer’s preference and the algorithm’s preference are no longer easy to tell apart, and that is the point.

The Indian wrinkle

The Indian version of this shift has its own shape, and at Kae we think it is the more interesting one.

First, voice and video unlock a different consumer. The buyer in Indore or Hubli or Guwahati was never going to type “lightweight breathable kurta for summer” into a search bar. But they will absolutely watch a thirty-second reel of someone showing them one, and click the link in the bio. Meesho today crosses 250M users, with roughly 87% of them coming from outside the top 8 cities. That is not a different funnel for the same customer. It is a different customer who only became reachable because the funnel itself changed.

Second, the platforms with the strongest feeds, Meesho, Instagram, YouTube, Sharechat, do not yet look like the platforms with the strongest carts. The cart is still concentrated on Amazon and Flipkart, where the buyer arrives with intent. Whoever closes the loop between feed-grade discovery and Amazon-grade fulfillment in India builds something enormous. We think the market is one or two product cycles away from someone doing it well.

Third, the brands that win in this environment will not look like the brands that won the last one. They will be faster, weirder, less attached to category orthodoxy, and built by founders who understand that their real competition is not the brand next to them on the shelf, it is the eight seconds before the user scrolls past.

The agent layer is coming

If algorithmic feeds are the present, AI agents are the very near future. Within a couple of years, a meaningful share of routine purchases will be made by software acting on a user’s behalf. Reorders of groceries, replenishment of consumables, travel bookings, basic insurance, utility switches.

The forecasts here are aggressive. Gartner now projects that by 2028, roughly a third of digital user experiences will shift from native apps to agentic front ends, and that on the B2B side, around 90% of buying will be AI-agent intermediated, pushing more than $15 trillion of spend through agent exchanges. Even if you take a heavy discount on those numbers, the direction is unambiguous.

The agent will not scroll, it will not be charmed by a reel, and it will not care about a founder story. This is the second power shift, stacked on the first, and almost nobody in consumer is ready for it. The skills that matter when you are selling to an agent are: structured data, verifiable claims, machine-readable reviews, API-accessible catalogues, and the ability to win on price-quality at the SKU level. Brand equity matters less. Persuasion matters less. Being legible to a model that has been told “find the best one” matters a lot.

If feeds turned brand building into recommender training, agents will turn it into something closer to SEO for machines. The brands that quietly invest in structured product data over the next eighteen months will look prescient by the end of the decade.

What survives

It is tempting to read all this as the end of human choice, which it is not. People are still going to want things, and at least some of those wants will be deep enough to drive search-style behaviour. Higher-consideration categories, luxury, identity goods, things worn in public, things put inside the body, will retain something of the old architecture. The shelf is not dead everywhere.

But the centre of gravity has moved, and it has moved in a direction that almost no one in consumer marketing has fully internalized. The default mode of consumption is becoming passive, ambient, and machine-mediated. The companies that are honest about that will build differently. They will hire data scientists where they used to hire creative directors. They will optimize for the algorithm’s tastes the way they used to optimize for the customer’s. They will accept that the salesperson now lives inside the platform, and the only question is whether it likes their product.

This may very well be the last generation that thinks of itself as choosing. The next one will be chosen for, gently, constantly, and with frightening accuracy. Whether that is a tragedy or just a different way of being a consumer depends on who you ask. At Kae, we mostly care about what gets built next. And what gets built next will be built for the machine first, the human second, and the shelf not at all.

What To Build: Fintech

Posted on May 11, 2026May 11, 2026 by Kae Team

Part two of the ‘What to Build’ series. We did consumer AI first because that was where the anxiety was loudest. We are doing fintech second because that is where the opportunity is least understood.

The “fintech is over” reflex is wrong, and quite badly.

Here is the conventional wisdom in any founder WhatsApp group in April 2026. Payments are commoditised; UPI killed the market. Lending is over-funded and the RBI is choking the consumer book. Neobanks have failed. Insurance is impossible. Wealth tech is a Zerodha and Groww duopoly. The conclusion: fintech is done.

This take is wrong on every clause. It conflates the death of one consumer fintech playbook with the death of fintech itself. The previous wave was about layering one feature (UPI rails, BNPL, P2P lending, low-cost broking) on top of an underdeveloped consumer market. That wave is genuinely tapped out. The next wave is being built on top of an entirely different stack, and almost no one has noticed.

Consider what India shipped in the last twenty four months. The Account Aggregator framework now has more than 110 million linked accounts and consent volumes growing at three percent week on week. The Unified Lending Interface began moving from agricultural pilots into MSME and personal credit, with disbursal times collapsing from four to six weeks down to under ten minutes in early production deployments. The new Digital Personal Data Protection Act, the revised co-lending norms, and 100 percent FDI in insurance all landed in the last eighteen months. India received 137 billion dollars in remittances in 2024, the most of any country in history. The 63 million MSMEs in India still represent a 530 billion dollar credit gap. Twelve million gig workers have less than fifteen percent formal credit penetration. Retail wealth is one third of GDP and the average Indian household still allocates two thirds of net worth to gold and real estate.

Read those numbers slowly. India in 2026 has more usable financial primitives than the United States. It has a larger underserved credit population than any country on earth. It has a diaspora that sends home more money than the FDI book and almost no fintech that serves them as customers rather than as remittance pipes. The “fintech is done” take is just an artefact of having looked at the wrong layer of the stack.

The list below is the layer we think is open. Same principles as the consumer AI piece. Twenty ideas, India-first and globally relevant where the unit economics travel, written for founders who actually want to build, not for decks. Each idea passes a four-part test: a real cohort with budget, a wedge that compounds with use, a why-now that did not exist eighteen months ago, and a non-obvious watch-out. None of these are easy. All are buildable today. We have tried to be specific about who wins.

If you are building one of these, or a sharper version of one of these, come talk to us.

1. The MSME underwriter on GST, AA, and ULI

There are 63 million MSMEs in India. Only 14 to 16 percent have ever received formal credit. The credit gap is approximately 530 billion dollars. The reason is not capital scarcity. The reason is that the marginal cost of underwriting an MSME for a 5 lakh working capital loan was, until recently, higher than the lifetime expected interest income. Banks could not justify it.

ULI broke that equation. With GST returns, bank statements via Account Aggregator, and credit bureau data flowing in real time through a single consent layer, an underwriter can now assess a small business in minutes for a fraction of the previous cost. The infrastructure is there. The product is not.

Build a vertical-specific MSME underwriter that combines the new data sources with proprietary cash flow signals from a specific industry. Start with one vertical (kirana, restaurants, salons, automobile workshops, pharmacies) where you can build a deep pattern library of revenue and stress signals. Lend off your own balance sheet via an NBFC partnership initially, then graduate to co-lending with banks under the new RBI norms.

Why now: ULI plus AA plus GST plus DPDPA is finally a closed loop. Two years ago, the data was either not consented, not standardised, or not real time. All three are solved.

Who wins: a founder pair with one credit person who has actually run a portfolio through a bad cycle, and one technical founder who can build the data pipelines. Not a marketplace founder who underestimated what underwriting actually means.

Watch-outs: do not underwrite at scale before you have lived through one cycle of stress in your chosen vertical. The losses on month 18 will define whether you are a real lender or a vintage-2026 statistic.

2. Vertical embedded credit for B2B software

A B2B SaaS company in India sees the entire transaction history of its customers. A pharmacy management software knows how much each pharmacy bills, what it owes its distributor, and what its working capital cycle looks like. A logistics platform knows which fleet operator has consistent payments coming in next week. None of them currently lend, because lending is hard and they are software companies.

Build an embedded credit infrastructure that lets vertical SaaS companies offer credit to their customers without becoming lenders themselves. The product is a B2B platform. You handle the underwriting using the platform’s data and AA, you handle the regulated entity (NBFC partnership or in-house licence), the SaaS company handles the relationship and the distribution. Revenue split. The SaaS company gets a new monetisation lever. The customer gets credit that actually understands their business. You get scale through the SaaS company’s existing distribution.

Why now: the new RBI co-lending norms make these arrangements far cleaner than they were even a year ago. Vertical SaaS companies are now mature enough (10 to 100 crore ARR) to want a credit revenue stream.

Who wins: a founder with both fintech and B2B SaaS DNA. Pure fintech founders underestimate how hard distribution is. Pure SaaS founders underestimate how hard credit is.

Watch-outs: pick three verticals and go deep. The temptation to be a horizontal embedded credit player kills companies. Stripe’s lending product took a decade to expand; you do not have that runway.

3. Healthcare lending at the point of care

Indian households spend roughly 50 percent of healthcare costs out of pocket, the highest share among large economies. A hospitalisation or major procedure routinely wipes out savings or pushes families into informal debt. Hospital tie-ups with NBFCs exist but are clunky, slow, and limited to chains. The point-of-care moment, where a family is being told they need to pay 2 lakh in the next 24 hours, is one of the most acute willingness-to-pay moments in the entire Indian economy and almost no fintech serves it well.

Build a point-of-care lending product that lives inside hospitals, diagnostic chains, and IVF centres. Approval in under five minutes using AA. Repayment plans that align with cash flow rather than calendar months. A back-end that integrates into hospital billing software so the loan is invisible to the patient until the conversation. Credit life insurance bundled.

Why now: every major hospital chain in India has gone digital with billing in the last two years. Account Aggregator coverage of the salaried middle class crossed a usable threshold in 2025. Together they make in-the-moment lending operationally viable.

Who wins: a founder pair who can actually sign hospital chains. This is half product, half enterprise sales. Without the relationships, the product never reaches the patient.

Watch-outs: this is a category where collections are the entire business. A patient who took a loan for cancer treatment is a different collections psychology from a personal loan default. Build the empathy into the recovery process from day one or you end up on the wrong end of a Mint expose.

4. The study abroad financing product

One million Indians apply to study abroad every year. The average US graduate program costs 60 to 80 lakh rupees. The current education loan market is dominated by HDFC Credila, Avanse, and Auxilo, products built for a more analog era, requiring co-applicants, collateral, weeks of paperwork, and rigid disbursal schedules. The market is begging for a digital-first product.

Build an education loan product designed entirely around the student journey. Pre-approval at the application stage based on the student’s profile and target school. Co-applicant flow that uses AA rather than physical paperwork. Disbursal directly to the university. Tuition paid in dollars at preferential rates through the cross-border layer. Optional living-cost top-ups. A repayment structure that defers principal until graduation plus six months. The full product is the financial companion across the eighteen-month admission-to-arrival journey.

Why now: PA-CB licences from RBI now make legitimate cross-border tuition disbursal possible without the friction of the previous correspondent banking flow. The Indian middle class is sending students abroad at unprecedented rates, and the willingness to pay for a clean financial product is high.

Who wins: a founder with strong credit DNA paired with someone who has either gone through the process themselves or worked at one of the existing lenders.

Watch-outs: the political environment in destination countries (US visa rules, UK student work rights) materially affects default rates. Build the model with a real understanding of how cohort default behaves under macro stress, not under steady-state assumptions.

5. Working capital for Indian exporters

India’s services exports crossed 350 billion dollars in 2024. Goods exports added another 450 billion. Roughly 200,000 small Indian exporters are sitting in a structural cash crunch: they ship product or deliver services, get paid in 30 to 90 days, and need bridge capital to fulfil the next order. The current options are restrictive bill discounting from banks, slow LCs, or expensive private working capital. Wise and Skydo solved the inbound payment leg. The financing leg is open.

Build a working capital product for the Indian exporter. Underwrite the receivable using verified buyer data and the export documentation. Finance against the verified invoice in 24 hours. Settle in INR or hold in USD as the exporter prefers. Recover from the inbound payment when it lands. The product is invisible if done right. The exporter ships, draws, and repays as cash flows in.

Why now: PA-CB licences and Skydo, Payoneer, Wise, and the new RBI cross-border framework have collectively opened up the data layer required to underwrite an Indian exporter. Platform-based exporters (Amazon Global, Etsy, Upwork, Toptal) have full transactional visibility that did not exist five years ago.

Who wins: a founder with trade finance experience or a deep payments operator. This is not a generalist consumer fintech play.

Watch-outs: forex risk and counterparty risk are real and unforgiving. A few large bad debts can sink the book. The team that takes risk management seriously wins. The team that treats this as a software arbitrage does not.

6. AI-native, humane debt collections

The single ugliest part of Indian fintech in 2024 was collections. Aggressive call centres, public shaming on social media, harassment of family members, occasional violence. The RBI cracked down hard in 2024 and 2025. Most lenders are now scrambling to clean up their collections function while maintaining recovery rates. The category is broken and the regulator is watching.

Build an AI-native collections product that works at scale and behaves with dignity. Voice agents that genuinely listen, understand a borrower’s situation, and offer realistic restructuring. Personalised payment plans generated in real time based on cash flow patterns from AA. Multilingual outreach that respects regional norms. Escalation flows that are calibrated to financial stress, not to recovery KPIs. Sell as a SaaS plus revenue share to lenders.

Why now: voice LLMs in Indian languages crossed a usable bar in 2025. The regulatory cost of bad collections jumped sharply. Lenders are actively shopping for solutions.

Who wins: a founder who has either built a collections function inside a lender or is a domain operator who has seen the bad version up close. This cannot be built by people who think collections is a routing problem.

Watch-outs: do not over-promise on recovery rates. The honest pitch is that you maintain or marginally improve recovery while sharply reducing complaints, regulatory risk, and reputational damage. That is a real product. A product that promises higher recoveries through pressure is the old playbook in a new wrapper.

7. The next-generation credit bureau

CIBIL, Experian, Equifax, and CRIF dominate the Indian bureau market. Their data is bank-centric, lagging, and increasingly inadequate for the new credit cohorts: gig workers, new-to-credit borrowers, exporters, MSMEs with cash-heavy operations. The RBI’s tightening of unsecured retail lending in late 2023 exposed how thin the existing scoring models were when stressed. Lenders are paying for bureau pulls but underwriting on a parallel set of alt data they have hacked together themselves.

Build the next-generation bureau as a product, not as a regulatory body. Combine traditional bureau data with AA cash flow patterns, GST returns, platform earnings (Ola, Uber, Swiggy, Zomato, Meesho, Amazon, Upwork), telco signals, and verified employer data. Sell to lenders as an underwriting layer. The output is not a single score but a structured risk vector with explainability. The compounding moat is data.

Why now: AA volumes crossed a usable threshold in 2025. Multiple alt-data sources are now consented and clean. The bureaus have been slow to integrate them. The window is now.

Who wins: a founder with deep credit DNA paired with strong data engineering. Probably someone who has worked inside CIBIL or a major NBFC and seen the gaps from the inside.

Watch-outs: this is a regulated category and the existing bureaus will lobby aggressively. Build with a clear regulatory thesis, possibly via the existing CIC framework, and engage with the RBI early rather than late.

8. The financial OS for India’s gig workers

Twelve million Indians drive for Ola and Uber, deliver for Swiggy, Zomato, Blinkit, and Zepto, or run shifts for UrbanCompany. Less than fifteen percent have access to formal credit. Forty percent earn below 15,000 rupees a month. They are the most underserved consumer financial cohort in the country. KarmaLife and a handful of others have made a start, but the category is wide open.

Build a full financial OS for the gig worker. A neobank-style account that pulls earnings from multiple platforms. Earnings-linked credit that adjusts in real time. Health and accident insurance bundled at thin premiums. Auto-savings into a micro-SIP linked to busy days. Term life for the worker’s family. Emergency credit that disburses in fifteen minutes when a medical or vehicle emergency hits. Voice-first support in regional languages. Pricing simple, transparent, free at the base tier.

Why now: India Stack components (AA, OCEN, ULI, eKYC) plus platform API access plus voice LLMs in Indian languages plus the new gig worker welfare framework introduced in the 2026 Budget all combine for the first time.

Who wins: a founder who has lived alongside this cohort, not someone optimising on a TAM slide. The product trust is built by going to driver canteens, not corporate offices.

Watch-outs: the platforms (Ola, Swiggy) will sometimes try to build this themselves. The right answer is to be the worker-side product, with the platforms as data partners. Picking sides between the worker and the platform is the most important strategic choice in this category.

9. The wealth coach for the UPI generation

A generation of Indians born after 1995 has grown up with UPI, Zerodha, Groww, and SIPs. They are saving and investing earlier than any previous generation. They are also making consistent, predictable mistakes: over-allocation to direct equities they do not understand, under-allocation to tax-advantaged products, near-zero allocation to insurance, no estate planning, no goal alignment. Zerodha and Groww built the rails. They did not build the coach.

Build a personal wealth coach for the salaried 25 to 40 cohort. Onboard via AA so you see the full picture of bank balances, mutual funds, stocks, EPF, and credit. Give honest advice, not product pushes. Optimise tax with a real understanding of the user’s bracket and instruments. Run goal-based planning for marriage, home, and children with real probabilistic models. Recommend term life and health insurance as the first product, not the last. Charge a flat fee, not a commission. Build trust by being the rare honest player in the category.

Why now: AA full-coverage, the SEBI investment advisor framework, and the maturity of direct mutual fund and ETF infrastructure together make a fee-only AI advisor feasible at retail prices.

Who wins: a founder who understands both the regulatory grain (SEBI RIA) and the product grain (consumer fintech). The credibility of the voice is the moat.

Watch-outs: do not optimise for AUM growth. Optimise for retention and Net Promoter. The wealth coach business compounds over decades. The team that thinks in years compounds. The team that thinks in quarters churns.

10. Wealth and decumulation for Indian retirees

India has 150 million people over the age of sixty and growing fast. Average household financial assets at retirement run between 25 and 75 lakh for the urban middle class. The product set serving this cohort is brutally inadequate: bank fixed deposits, postal savings, a handful of senior citizen schemes, and an LIC annuity book that is mispriced. The right product, decumulation planning that turns a lump sum into a multi-decade income with care for inflation, healthcare costs, and longevity, simply does not exist at scale in India.

Build a retiree wealth product. The first conversation is not a portfolio question; it is “how do you want to live for the next 25 years?” The product translates that into a structured income plan, allocates across instruments (bonds, debt funds, REITs, annuities, equity), layers in healthcare and long-term care planning, and maintains it. Charge a flat annual fee. Pay relationship managers to do quarterly check-ins, especially for users with no adult child managing their finances.

Why now: 100 percent FDI in insurance opened up annuity innovation. Bond and REIT retail availability has matured. The diaspora children of Indian retirees are willing to pay for their parents’ financial care.

Who wins: a founder with deep wealth advisory experience plus genuine empathy for an older Indian user. Most wealthtech founders are 28 and building for themselves. This product needs the opposite.

Watch-outs: do not let the children become the buyer and the parent become an afterthought. The product has to delight the seventy-year-old user. If the seventy-year-old does not log in, the product has failed regardless of who is paying.

11. The retail bond and private credit platform

Indian retail investors hold roughly 60 lakh crore in fixed deposits and another 40 lakh crore in small savings. The post-tax return is poor. The bond market is largely institutional. SEBI opened up retail access to corporate bonds in 2024 and to a wider private credit set in 2025. Wint Wealth, GoldenPi, and Tap Invest have started, but the category is still under-built.

Build the retail bond and private credit platform that India’s wealth-accumulating middle class deserves. Curate a clean shelf of corporate bonds, government securities, REITs, InvITs, and accredited private credit deals. Offer fractional access where the regulator permits. Provide credit ratings, default histories, and stress test outputs in plain language. Auto-allocate ladders for FD-style users who want a 7 to 10 percent post-tax yield without the lockup. Pricing flat, never commission.

Why now: SEBI’s revised framework on online bond platforms made retail access cleaner. The AA-driven income proofing for accredited investors is now operational. Distribution can finally scale without the broker call centre model.

Who wins: a founder with a real fixed income background plus consumer fintech distribution chops. This is not a category where you can fake the credit work.

Watch-outs: when the credit cycle turns, retail will get hit with defaults they did not understand. Your job is to over-disclose and to choose your shelf carefully. The first big retail default that lands on a platform without proper risk communication will set the category back five years.

12. The wealth product for the Indian SMB owner

The 1.5 to 2 million Indian SMB owners running businesses with 5 to 50 crore in annual revenue are uniquely under-served. Their wealth lives largely in business equity, real estate, and gold. Their financial advisors are the family CA, who optimises for tax compliance, not wealth creation. They are too small for a private banker and too big for a Groww account.

Build a wealth product specifically for the SMB owner. Personal balance sheet that integrates business equity, household assets, and liabilities. Tax planning that optimises across personal, business, and family. Succession and inheritance structuring (HUF, LLP, family office light). Portfolio allocation that recognises the concentration risk in their business and counterbalances. A service tier with a real human relationship for the moments that matter (acquisitions, exits, divorce, disputes).

Why now: AA, GST, and corporate filings make a unified wealth view possible for the first time. Demographic transition, the second generation taking over the business, has created a willingness to professionalise.

Who wins: a founder who has been a wealth advisor in a private bank or has come out of a CA practice that served this exact cohort. Credibility is the product.

Watch-outs: the buyer makes decisions slowly and emotionally. Do not over-engineer the onboarding. The first three meetings are about trust, not features. Build the product to be patient.

13. The full-stack NRI bank

India received 137 billion dollars in remittances in 2024, the largest remittance flow to any country in history. The Indian diaspora numbers 35 million, including 16 million NRIs. Most of them bank in their country of residence and remit to India. None of them are well served by either side. Indian banks treat NRIs as a low-touch deposit base. Foreign banks treat them as a marketing segment. Nobody has built the product the actual NRI wants: a single financial home across two countries.

Build a full-stack NRI bank. Multi-currency accounts (USD, GBP, AED, SGD, INR) with FX at near interbank rates. NRO and NRE seamlessly managed. Mutual fund and PMS investing in India with KYC, FATCA, and PFIC handled in software. Real estate investment with end-to-end legal and registration. Tax filing in both jurisdictions. Estate and inheritance planning across borders. Concierge for the parent in India who needs help with anything (from a hospitalisation to a property dispute).

Why now: the diaspora is wealthier, older, and more willing to pay for service than at any prior point. RBI’s revised NRI account rules and the new tax framework on foreign remittances both landed in 2025, opening up product space.

Who wins: a founder who is themselves a sophisticated NRI or is married to one. The product nuances are buried in lived experience.

Watch-outs: regulation in two jurisdictions is harder than founders expect. Do not start with twenty geographies. Pick US-India or UAE-India and own that corridor before expanding. Each corridor is a different product.

14. Cross-border payments for Indian SMBs

PA-CB authorisations from RBI in 2025 and 2026, granted to Wise, Payoneer, Skydo, and a handful of others, opened up the legitimate cross-border payments market for Indian businesses. Skydo has shown what is possible: tens of thousands of Indian service exporters on the platform, flat-rate pricing, zero forex markup. The category is no longer regulatory blocked. It is now a product and distribution race.

Build a cross-border payments product for a specific cohort that the current players underserve. Indian e-commerce sellers exporting on Amazon Global. Indian agencies serving global clients on retainer. Indian SaaS companies billing in dollars but operating in India. Indian creators monetising on YouTube and Substack. Each cohort has a slightly different set of needs around invoicing, recurring payments, and currency hedging. Pick one. Build the deepest product for that cohort. Expand later.

Why now: PA-CB regime is operational. Payment volumes are growing. The previous semi-legal corridors are shutting down, pushing volume onto legitimate rails.

Who wins: a founder with both payments operations DNA and a real understanding of one specific exporter cohort. Generalists lose.

Watch-outs: this is a high-volume, low-margin business. Unit economics matter from day one. A founder who plans to subsidise growth with venture capital will hit a wall when a more disciplined competitor underprices them.

15. Embedded insurance in commerce flows

The IRDAI’s 2025 framework and the rollout of API-driven insurance distribution have made embedded insurance commercially viable. PwC India estimates the embedded insurance market could exceed 2 billion dollars by 2026 and protect 100 million gig and mobility users in that period. Insurance bundled into a Swiggy delivery, an Ola ride, a Cleartrip flight booking, an Amazon order is now a real distribution channel.

Build an embedded insurance infrastructure that lets any consumer platform offer relevant insurance at the right moment in the customer journey. Mobility flows, e-commerce flows, travel flows, and utility flows each have different relevant covers. The product is a B2B platform that handles underwriting, regulatory compliance, claims processing, and fraud detection, while the consumer platform handles distribution. Revenue share with the platform.

Why now: IRDAI’s regulatory updates, the maturity of API-led insurance product design, and consumer comfort with thin, single-event insurance products all converged in the last 24 months.

Who wins: a founder pair with insurance DNA and platform partnership chops. This is a B2B sale to consumer platforms, then a regulated insurance operation underneath. Both halves are hard.

Watch-outs: claims experience is the make-or-break. A platform partner whose customers have a bad claims experience will turn off the integration in a quarter. Build the claims layer with the same rigour as the underwriting layer.

16. Parametric crop and weather insurance

Roughly 85 million Indian farmers depend on agriculture. Climate volatility has made the last five monsoons increasingly variable. Traditional crop insurance, primarily PMFBY, is plagued by slow claims, dispute, and corruption. Parametric insurance pays out automatically based on triggers (rainfall, temperature, satellite-derived crop health) without the slow human-driven claim assessment. The technology is finally cheap enough to deploy at India scale.

Build a parametric insurance product for Indian farmers. Use satellite data, weather station inputs, and on-ground IoT (where available) to define triggers per crop and region. Distribute through agri-input retailers, FPOs, and rural NBFCs, the points where the farmer already has a financial relationship. Settle claims directly to bank accounts via UPI or AePS. Bundle with crop loans for retention.

Why now: Bajaj’s ClimateSafe and a handful of pilots demonstrated the technical and operational viability in 2025. Satellite data costs have collapsed. IRDAI is encouraging the category. Climate risk is rising.

Who wins: a founder with deep rural distribution DNA paired with insurance and remote sensing capability. The hardest part is rural distribution. The technology is the easier half.

Watch-outs: parametric basis risk (the gap between the parameter and the actual loss) is real. Educate the farmer up front. A product that pays out when the satellite says “drought” but the farmer’s specific field had rainfall is a credibility disaster. Build the trust by paying out fairly even at the edges.

17. Insurance for chronic disease cohorts

Roughly 77 million Indians have type 2 diabetes. 200 million have hypertension. Tens of millions live with PCOS, cardiovascular conditions, asthma, and other chronic illnesses. Standard health insurance treats these as risks to price out. The right product treats them as cohorts to manage actively, sharing the upside of better management with the patient.

Build a chronic-disease-first health insurance product. Continuous monitoring through CGMs, BP cuffs, and connected devices. A care team (nutritionist, coach, doctor) included. Premium discounts for verified clinical improvement (HbA1c down, BP under control, weight in range). Claims paid via cashless network. Integration with the AI health concierge from the consumer AI list.

Why now: 100 percent FDI in insurance, IRDAI’s openness to outcome-based health products, and the dramatic drop in CGM and connected health device prices over the last 24 months together make this category technically and commercially viable.

Who wins: a founder pair with one healthcare insider (preferably a doctor who has seen the chronic care population in scale) and one insurance operator who can stand up the regulated entity.

Watch-outs: the unit economics are tight at the start. You will lose money on the first cohort. The bet is that better-managed members generate dramatically lower claims after year two. If you do not have the conviction and the capital to ride that, do not build this.

18. AI tooling for chartered accountants

India has roughly 400,000 practising chartered accountants. The CA serving the 5 lakh small business owners and the 15 million salaried filers spends most of their time on data entry, reconciliations, GST, TDS, and form filing. The actual advisory work that justifies their fees is squeezed by the operational load. The right product is not consumer accounting software. It is the picks-and-shovels tool that makes the CA dramatically more productive at scale.

Build an AI-native CA practice management product. Auto-import bank, GST, and platform data via AA and OCEN. Auto-categorise transactions with pattern learning. Auto-prepare and auto-file ITRs, GSTs, TDS returns, and ROC filings, with the CA reviewing and signing. Built-in client communication that drafts the right reminder at the right time. Pricing per CA seat, plus per filing. Distribution through ICAI bodies and regional CA networks.

Why now: AA and the GST API combined with capable LLMs make end-to-end auto-preparation viable. The CA is overwhelmed by compliance load and is genuinely shopping for tools.

Who wins: a founder with either a CA background or deep experience in a regulated B2B tooling category. The trust of the practitioner is the product.

Watch-outs: do not try to bypass the CA. The dream of “consumer self-filing replaces the CA” has failed for thirty years in India for good reason. The CA is a trusted relationship. Make them more powerful and you have a customer for life.

19. The AI compliance product for fintechs

Indian fintechs spend a stunning percentage of engineering and ops time on compliance. RBI guidelines change frequently, IRDAI now ships material updates every quarter, SEBI moves on its own cycle, and DPDPA layers a privacy regime on top. Most fintechs run compliance as a manual operation with a spreadsheet and a worried compliance officer. The cost of a bad call is regulatory action, which can mean a 30-day pause or a permanent shutdown.

Build an AI compliance product for the fintech sector. Continuous monitoring of regulatory updates with auto-mapping to a fintech’s products. Pre-built control libraries for KYC, AML, transaction monitoring, customer disclosures, and grievance redressal. Audit-trail-ready evidence packages. Voice or text agent that the compliance officer can ask in plain English. Pricing per regulated entity per month.

Why now: the regulatory cadence has accelerated. The compliance burden has become a real engineering and finance line item. LLMs are finally good enough to map regulatory text to product controls reliably.

Who wins: a founder who has been a compliance head inside a regulated fintech, paired with strong product engineering. Domain depth is non-negotiable.

Watch-outs: do not over-promise on automation of regulatory judgement. The product augments the compliance officer; it does not replace them. Sell that frame. The fintech that thinks they bought a replacement and gets fined will be vocal.

20. The corporate card for India’s SMBs

Razorpay X, Cred Escrow, Open, and a handful of others are building corporate cards and spend management for the Indian startup. Most stop at the funded startup tier. The 1.5 million Indian SMBs running 5 to 50 crore businesses, almost all of them bootstrapped or family-owned, are a different segment with no real product.

Build a corporate card and spend management product for the bootstrapped SMB. Underwrite based on GST, AA, and bank statements rather than on equity funding. Issue cards with line discipline (per category, per vendor, per employee). Auto-reconcile against GST input tax credit. Built-in vendor and employee reimbursement workflows. Bundle with payment gateway and working capital. Pricing based on transaction volume, not subscription.

Why now: GST input credit auto-reconciliation needs the GST API maturity that landed in 2025. AA and corporate filings allow underwriting without equity collateral. The SMB market has digitised payment behaviour materially in the last 24 months.

Who wins: a founder with deep SMB distribution chops, ideally from a payments or accounting background. This category lives or dies on the ability to acquire SMBs at low cost.

Watch-outs: the larger banks and the existing fintech leaders will compete hard once the segment proves out. Your edge is the depth of fit for the bootstrapped SMB and the efficiency of acquisition. Premium pricing or premium positioning will not work in this segment. Build cheap, build accurate, build trusted.

Picking one

Twenty ideas is a menu, not a strategy. Here is how we would think about narrowing if we were sitting across from a founder next Tuesday.

First, fintech is a regulated category and the regulator is a co-author of every product. The teams that win in fintech are the teams that go to the regulator early, listen carefully, and design within the lines. The teams that try to operate first and ask permission later have a one to two year window before they hit a wall they did not see coming. Pick a category where you understand the regulatory thesis cold.

Second, the unit economics are different in fintech. There is no growth-at-all-costs path. A fintech that loses money on every loan, every premium, every transaction does not turn the corner with scale; it turns into a bigger losing fintech. We wrote in January that companies which controlled burn and proved unit economics raised cleanly in 2025. That is twice as true in fintech. Build a model that is profitable at the loan or policy level on day one. Subsidise distribution if you must. Never subsidise risk.

Third, distribution is the moat in Indian fintech. The product layer is being commoditised. The data layer is being democratised. What is left is who acquires customers cheaply and retains them honestly. The categories above all have a specific distribution advantage attached: a vertical SaaS partnership, a hospital chain, a CA network, a retiree relationship. Pick yours up front. Without one, you are buying customers from Google and Meta at a unit cost that will kill you.

Fourth, fintech rewards founders who think in decades. The wealth coach, the chronic disease insurer, the NRI bank, the retiree wealth product are all multi-decade businesses with compounding trust as the asset. The crypto-era playbook of “ship fast, raise fast, exit fast” is a fintech graveyard. The team that can hold the line for ten years wins. The team that needs an exit in three should pick a different sector.

Finally, India in 2026 is not the India of 2018 in fintech terms. The infrastructure is genuinely better. The regulator is genuinely more thoughtful. The customer is genuinely more aware. The cliche of “this could only happen in India” used to be a cope. It is now the actual differentiator. Build accordingly.

We will follow up with what to build in vertical AI SaaS next, then AI infra. If you are building one of the twenty ideas above, or a sharper version of one, we want to hear from you.

A note on intent: this is a thought piece, not an investment thesis. We write to surface ideas worth thinking about and to start conversations with builders.