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From Mechanical Engineering to a $65K MRR D2C Company

Mechanical engineering degree. Semiconductor supply chains. Then Rishabh Harish co-founded Wellbi, a D2C bamboo apparel brand doing $65K monthly revenue serving 100,000+ customers. This is how systems thinking beats fashion school credentials.

January 12, 2026
15 min read
By Rachit Magon

Most fashion founders come from design schools. They've got portfolios, internships at fashion houses, and years understanding fabrics and fits.

Rishabh Harish studied mechanical engineering, interned at Oakley, managed semiconductor supply chains at Ksite Technologies in San Francisco, and then co-founded Wellbi - a D2C bamboo apparel brand in India.

Today, Wellbi has served over 100,000 customers with $65,000 in monthly recurring revenue. They're not competing on design complexity. They're competing on fabric innovation, supply chain efficiency, and customer obsession learned from building precision parts for semiconductors.

This is the story of what happens when you bring systems thinking to a category that's always been about aesthetics. Spoiler: the systems win.

Key Takeaways: When Engineering Meets Fashion

The Non-Fashion Advantage:

Customer Discovery Over Design:

The D2C Unit Economics Reality:

Q: You studied mechanical engineering, worked in semiconductors. How do you end up building a fashion brand?

Rishabh Harish: My dad is a businessman, so entrepreneurship was always in the back of my mind. Coming to the US for my masters was about exposure - understanding how the market works, especially in California where the tech and startup ecosystem is massive.

After my job, I moved to SF, the tech hub. Just the ecosystem helped me get into the startup world. I wanted to start something since my masters. I came across my current co-founder who had started Wellbi five years ago and was seeking investment.

I thought, okay, I can invest, but I also want to be part of the journey. One condition - I'd work along with them to grow the company. Since then, we've grown five times in revenue, the valuation has grown amazingly, and we've raised some money.

🔥 ChaiNet's Hot Take: The best investments aren't checks. They're when you bet money AND time on the same thing.

Q: D2C is brutal. What made you think you could compete without a fashion background?

Rishabh Harish: When I joined, we were selling handwoven shirts. The supply chain was complicated, lead time was very high, and we were significantly different from other companies. Product-market fit was very tough. We only got sales when we gave discounts - that's not sustainable.

We thought, okay, we aren't doing well on growth, we're burning money. How about we turn our company into something that's actually value-added? Something customers want to come back for. That's what every startup needs to focus on - a niche that other companies aren't offering.

We came across bamboo fabric, a bamboo-cotton blend. Amazing fabric. We thought, why not introduce that to the market? We're completely different, no one else is doing it. We introduced it alongside our existing shirts, and we got amazing reaction. That initial validation - people coming back and purchasing more - that's when we realized, okay, why don't we double down on just selling t-shirts?

We stopped production on shirts and went all in on t-shirts. Took a bet.

🔥 ChaiNet's Hot Take: Fashion school teaches you to make beautiful things. Engineering teaches you to make things that work. Wellbi bet on the second.

Q: How do you make product decisions without a design background?

Rishabh Harish: We had a fashion designer, Sangeeta, working with us - a fresher. As a startup, we can't afford experienced designers, right? I'm very focused on making things productive and efficient, so I pushed the team to use tools.

For example, Perplexity helps us do competitive analysis, look at trends, review articles. The best data is on Myntra and Amazon. You can see companies doing well, who has most sales. There are tools to understand who's doing amazing.

AI helps us understand patterns for what we want to release next. But we're not too dependent on AI because we focus on basic essentials - polos, innerwear. We're doing fabric innovation. We're not style-oriented yet. We take what's out there in the market, change the fabric, make it more comfortable. That's been the goal.

🔥 ChaiNet's Hot Take: When you can't compete on design complexity, compete on material science. That's an engineer's natural advantage.

Q: You mentioned using Helium for Amazon research. How does that work?

Rishabh Harish: Helium is an amazing tool. Let's say you're selling t-shirts and want to make sure there's a market. You go into Helium, look at competitors. It has a plugin - as you scroll through Amazon, it gives you revenue predictions based on data they pull from Amazon.

You can see if a product is doing $1 million, or in India, 10 lakhs, 20 lakhs. Some companies are selling one product and doing crores. You get all that data, see which keywords are working, because Amazon runs on keyword marketing.

If you want to create something new, go to the niche you're looking at, look at reviews, understand what complaints people have about that specific product. Find the common complaints, solve that particular problem in your product. It's as simple as that.

🔥 ChaiNet's Hot Take: Fashion designers start with mood boards. Engineers start with complaint analysis. Different paths, but complaints are more honest than inspiration.

Q: Does your supply chain background show up in how Wellbi operates?

Rishabh Harish: Definitely. Any engineering background or work experience really helps. That's why founders say work at a company for five years - understand how things work. It shapes your mind. How to organize, communicate, build a company, understand hierarchy, management, decision-making.

As a mechanical engineer, I learned analytical skills, logical skills. My mind is trained to do certain things. We're in materials and fabrics, so that definitely helps. Data analytics to make decisions - an engineering mind is trained for that.

My actual work experience is supply chain. I understand demand, sourcing from across the world. In semiconductors, parts are expensive and require precision accuracy. What we're doing with D2C is nothing compared to that.

Understanding demand, working with vendors, negotiating price, writing contracts, having multiple vendors for resiliency - if one doesn't work, you go to the second. All of this helps build supply chain resiliency. Dealing with people around the globe, especially Europe where they're very strict with quality - I feel I'm also very strict with vendors. Indian vendors don't like it, unfortunately.

🔥 ChaiNet's Hot Take: Hospitality founders obsess over experience. Tech founders obsess over product. Supply chain founders obsess over what never breaks. In D2C, what never breaks wins.

Q: You found something surprising - men are easier to sell to than women in fashion. Explain that.

Rishabh Harish: We had a viral moment. The founder of Fredo, Ganesh, tweeted about our product. It went viral. We got 3.5 lakhs worth of sales within 24 hours, organically. That was one year ago.

I realized - people need validation. If someone known talks about your product, they'll buy. And men, once they buy, they stick with you forever. That's good about acquiring men as customers, which we focused on initially.

Then women customers came and said, "Hey, why don't you have this for us?" That's when we started releasing women's t-shirts, crop tops, polos.

Most online D2C consumers are men. They're willing to take bets as long as they trust the brand. You can sell to men at any price if they trust you. Women are more price-sensitive because they have so many options - 100, 150, 200, 250, 1000 rupees. Why choose 1000 unless...

Women are more focused on design, style, pattern. Men just want simple, comfortable things. That's a fact.

🔥 ChaiNet's Hot Take: Men's loyalty comes from simplifying decisions. Women's loyalty comes from exceeding expectations. Different games, different playbooks.

Q: What's the real unit economics of D2C fashion that people don't talk about?

Rishabh Harish: Let me break it down. 30-35% is cost of goods sold - the cost to manufacture. That can go up to 40% if we give discounts. 10% is shipping and warehouse. The majority, 30-40%, goes to Meta. That's customer acquisition cost.

So in our category, you spend 30-35-40% of the selling price to get someone to purchase. Post-purchase, you can do WhatsApp marketing, which is much cheaper. But this is the reality - it's not easy. Big D2C companies have lost money for two-three years. Some shut down.

In the US, acquisition cost goes up to 50-60%, sometimes 100%. That's why D2C prices are so expensive there. You need to make up that acquisition cost through lifetime value from the customer. From the first product, you might actually lose money.

If you're a new brand, it's brutal. Meta has so much competition. Since we started two years ago, we've almost reached a point where we can scale, but it's much more challenging for new D2C brands. There's no other avenue - it's a necessary evil.

🔥 ChaiNet's Hot Take: D2C isn't "direct to consumer." It's "debt to customer acquisition, then profit through retention." Plan accordingly.

Q: How do you use AI at Wellbi?

Rishabh Harish: I believe in keeping the team lean. Not involving many people helps with margins and profits. We use AI in several ways.

Six-eight months ago, we started using AI agents to talk to customers. Initially, we had a customer service rep, but Indian customers love asking questions even though answers are on the website. Our rep had to answer the same questions all the time.

We introduced AI to answer commonly asked questions. We prompt it, give it website data, add specific unique questions. It answers everything. It saved our customer rep 60% of their time. Only when things escalate does it move the chat to an actual representative - for refunds, complex issues.

Anyone I try to hire, I ask, "Do you use Perplexity or ChatGPT in everyday life?" Some haven't even come across these tools. Even if they don't know, I want them to learn. It helps their career and makes things easier for us as a lean team.

I'm currently looking at demand forecasting - understanding inventory levels, when to place orders, automating it. That's challenging. I came across one startup, but didn't see results because if you put in bad data, it spits out bad data. There's a big gap there. If any company is solving demand forecasting for D2C, please reach out.

🔥 ChaiNet's Hot Take: AI doesn't replace customer service. It filters for what actually needs human attention. That's not automation, that's triage.

Q: What broke first when you started scaling?

Rishabh Harish: A lot of things you can figure out by hiring people, which requires funding. But I'd say D2C is all about supply chain and cash flow management.

We had a longer lead time for bamboo fabric because it's not something you can buy at wholesale and stitch. It's made-to-order. You need to convey demand to your supplier. It takes much more time than cotton or polyester to knit.

That's where we found a bigger challenge. We used to run out of bestselling SKUs like chocolate brown all the time. We'd lose money. When you run out of stock, Meta doesn't give you good conversion. The entire thing breaks down.

That's why understanding demand and placing orders correctly is critical. Not ordering too much because you'll pay for warehouse. It's a balance. It's where a lot of founders fail and lose revenue.

🔥 ChaiNet's Hot Take: In D2C, running out of stock doesn't just lose today's sale. It resets your algorithm momentum. The real cost is invisible.

Q: Let's talk about the brutal numbers. $65K MRR sounds great until you break down the economics.

Rishabh Harish: Yeah, let me break it down. 30-35% cost of goods sold, depending on quality and selling price. Sometimes 40% if we're giving discounts. 10% shipping and warehouse. Then 30-40% to Meta - that's where most D2C relies on for acquisition.

After that, there's tax - like 10% of tech costs for running on Shopify, payment gateway commissions. If you're running on Amazon or Myntra, you give 20-25% of selling price to them as fees. Plus Amazon requires ad spend, so margins shrink. Amazon is for volume, not for making money. Very few people make money there unless you're selling thousands per day.

Since we're omnichannel, we focus on Amazon because people trust Amazon and Myntra more than D2C websites. They come across our ad and look us up there. That's fine - at least we're not losing the customer.

Three-four months ago, 90% was website, 10% was B2B and other platforms. Now I'm focusing on Amazon and Myntra so we can start scaling there. It's an amazing platform if you leverage it right.

🔥 ChaiNet's Hot Take: D2C margins are a mirage until you account for retention. The business model isn't first purchase profit - it's third purchase cumulative profit.

Q: What's your WhatsApp marketing 101 for new founders?

Rishabh Harish: If you're doing WhatsApp marketing, you're already lucky - you got your first few customers. Congrats. WhatsApp marketing is about right timing. Send messages after work, in the evening, when people are active and hopefully in a shopping mood.

Give special discounts. Acquiring a new customer costs 30-40%, right? Why not give existing customers 10-20% discount? You're still not losing even at 25%. You already acquired them.

Work on when to send. End of the month? They've run out of money. Send on the second, when salaries are deposited. Special occasions, festive seasons - focus there.

The copy matters. Sometimes send as a founder - "Hey, founder here. Thank you for purchasing." Very personalized notes are important. Good images, short, tiny, capturing attention.

We use tools like Refresh for affiliate marketing. If you've purchased, share with friends, get 15-20% commission, your friend gets extra discount. That's better than Meta if you have good communities.

For WhatsApp tools, we use SagePilot.ai. Young founders, they ship products amazingly fast, take feedback, work on it overnight. They're introducing AI calling for abandoned carts - imagine getting a call saying, "You have this product in cart, why don't you purchase? Is there any problem? Here's extra discount." Not sure how people will react, but we'll test.

🔥 ChaiNet's Hot Take: Email is dead for D2C in India. WhatsApp is king. Not because it's better tech, but because it's where your customers already live.

Q: If someone with an engineering background wants to start D2C in a category they don't know, what would you tell them?

Rishabh Harish: First thing - get a good mentor in that space. If I were to start all over again, I'd talk to D2C founders, understand the challenges. Not to demotivate, but to understand reality - Meta costs, all these things.

If possible, intern there for a month, six months to a year. Understand how things work. Do you like doing it? This is not a short-term game. It's long-term.

A lot of founders are talented but fail at the end because they don't have that knowledge. They think they can learn using their own experience, but it takes time. How many times can you fail? By then, you've run out of money.

The best thing? Be a founder's office person for a year, year and a half. Don't care about the money. People say, "I need this much salary because I have an MBA." No. It's experience. I've learned by investing money. This knowledge is worth it. Even if I go out for a job, big companies will hire me because of detailed knowledge I've gained.

One of my ex-Twitter friends started a women's ethnic sandals company. Amazing design, but it didn't work out - maybe unit economics. He struggled, but now he just became co-founder at Jaipur Rugs. Great opportunity. Now he has access to money, people he can hire. It's a turning point.

Work, be dedicated, be patient. This is a long game.

🔥 ChaiNet's Hot Take: Fashion school gives you credentials. Founder's office gives you scar tissue. In D2C, scar tissue is more valuable.

Final Thoughts: Systems Thinking Beats Fashion Credentials

Rishabh's lesson on fundamentals: The barriers to entry in D2C are lower than ever. Anyone can set up a Shopify store, run Meta ads, source products. But the barriers to building something real? Those are still there. Unit economics. Supply chain resilience. Customer obsession. Systems thinking.

The bottom line: Rishabh didn't go to fashion school. He studied engineering, worked in supply chains, and applied that rigor to building Wellbi. His advantage isn't that he succeeded without fashion expertise - it's that his engineering background, understanding of operations, and supply chain experience became advantages in a category that's usually chaos.

Whether you're using AI tools to fill gaps in expertise, applying systems thinking from one industry to another, or building D2C in emerging markets, the lesson is the same: traditional expertise matters less than discipline, thinking, and willingness to learn.

You can find Rishabh on LinkedIn and check out Wellbi's bamboo apparel at wellbi.in. This is what happens when you bring precision engineering mindset to fashion - not more beautiful clothes, but clothes that solve real problems with material science, not marketing.

Q: How can people connect with you and learn more about Wellbi?

Rishabh Harish: You can find us at wellbi.in. We're building essentials for people who care about comfort and quality over flashy designs. If you're tired of fast fashion that falls apart, if you want products that actually feel different because of fabric innovation, check us out. You can also connect with me on LinkedIn - always happy to talk D2C, supply chain, or just the realities of building in India.

Final words: The most dangerous assumption in business is that credentials predict success. Rishabh had zero fashion credentials. What he had was customer obsession learned from hospitality, precision thinking from engineering, and supply chain rigor from semiconductors. He took those "irrelevant" skills and applied them to fashion. The result? 100,000+ customers and $65K MRR. Your background isn't irrelevant - you're just applying it to the wrong problems. Find the right problem, and your "irrelevant" background becomes your unfair advantage.


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