An interview with Tengin founder Madhu on turning coconuts into a business built around farmers, villages and communities.
Updated
June 1, 2026 1:46 PM

Workers of Tengin. PHOTO: TENGIN
In Southern India, coconuts are part of daily life. They are used in food, rituals, farming and home remedies. For Tengin, a social startup whose name means “coconut” in Kannada—a South Indian language—the crop also offers a way to build a rural business with deeper local impact.
Founded by Madhu Kargunda in 2017, Tengin works with farmers, artisans and women’s collectives in Karnataka to make products from almost every part of the coconut. Its range includes virgin coconut oil, desiccated coconut powder, shell-based handicrafts, candles, home décor items and other coconut-based goods.
The larger idea is simple. Farmers should play a bigger role in the value created from the crops they grow. Tengin is trying to help rural communities move beyond supplying raw produce and take part in processing, branding, packaging and sales.
Madhu grew up in an agricultural family. Over the years, he saw many young people move away from farming to look for stable jobs in cities. To him, the problem was not farming itself. The bigger issue was that farmers often missed out on the value created after crops left the farm.
A coconut might be grown in a village, but much of the income comes later through processing, branding and retail. That gap stayed with him, eventually leading him to leave his eight-year career in IT and return to agriculture full-time.

Started with just making virgin coconut oil, Tengin has grown into a wider coconut products business. The startup is now working with around 15 to 20 farmers and artisan groups across Karnataka. It is also building production capacity for larger retail and B2B partnerships.
Today, Tengin generates annual revenue of roughly ₹50-60 lakh, or around US$52,000 to US$62,000. It has also started testing international demand, including a recent export of around 200 kilograms of desiccated coconut powder to Texas.
As Tengin expanded, the team began looking more closely at parts of the coconut that were usually treated as waste or low-value byproducts, such as coconut shells and coir. At first, Tengin treated them that way too.
“When we started, we used to burn some of the shells”, Madhu said. “Later, we realized it was an economic opportunity”.
That changed the company’s product strategy. Local artisans working with Tengin now are turning coconut shells into bowls, incense holders, candles, coffee mugs, mobile stands and handcrafted décor items.

This gives Tengin a place in the circular economy, where waste materials are reused instead of thrown away. For Madhu, though, sustainability has to do more than reduce waste. It should also create income in the community.
“We wanted to minimize waste and maximize wealth locally”, he said.
Tengin does not depend only on one central factory. Instead, it works with smaller village-level production groups that connect to a larger business network. This helps farmers stay close to their land while also taking part in processing and manufacturing. It also creates local jobs, which can reduce the pressure to migrate to cities.
Yet, the model is not always easy. In the early days, Tengin had to convince some farmers to move from chemical farming to natural farming. Moreover, the weather has also become harder to predict. Irregular rainfall and changing harvest cycles can affect coconut prices and production consistency.
Still, Madhu sees the village-based model as central to Tengin’s identity. For him, villages are living systems built on shared work, local knowledge and interdependence.
“The definition of a village is inclusiveness”, he said.

That belief also shaped Tengin’s “coco tourism” initiative. Through the program, visitors meet farmers, learn about farming practices and see how coconut products are made.
During one visit by MBA students from Indiana State University, an unexpected spell of rain gave the group a closer look at village life. Farmers gathered and began singing traditional folk songs to express gratitude to nature. For the students, it became a lesson in culture as much as business.
Madhu sees these moments as part of what rural entrepreneurship can protect.
“If villages become empty, we lose language, traditions and local knowledge too”, he said.
Tengin’s model is not difficult to copy on paper. Madhu is open about that.
“Anyone can do it”, he said, “but what matters is how you work with people”.
For him, the harder part is building long-term trust with farming communities. Tengin works through relationships more than rigid contracts. This encourages farmers and local groups to participate in the system in a more collaborative way.
That trust has become one of the startup’s strongest assets. It shapes how Tengin works with producers and how it presents its products to customers.
For Madhu, it is not enough to call a product sustainable. Customers should be able to understand where it came from, who made it and how their purchase supports the people behind it.

That matters even more in a market where terms like “eco-friendly” and “organic” have become buzzwords. Madhu knows that these words can feel empty when brands do not show what they actually mean.
“Anyone can use these words today,” he said. “What matters is whether consumers can actually see what you are doing”.
This is why Tengin focuses on transparency and storytelling. The startup wants customers to see the full journey of each coconut product, from the farm to the finished item. It also wants them to understand whose livelihood is connected to that journey.
Madhu also believes small brands cannot depend on products alone. Products can be copied, but a clear story, a trusted community and a visible impact are harder to replicate.
“Don’t try to sell only the product,” he said. “When you try to sell the product, you are being sold once”.
Each Tengin product includes details about the people behind it and how profits are shared. In that way, the company connects its coconut products to the farmers, artisans and village systems that make them possible.
For Madhu, entrepreneurship starts with the problem. Founders, he believes, should understand the problem deeply before thinking about scale and revenue.
“An entrepreneur is someone trying to solve an existing problem”, he said. “Sometimes it may be a small problem, sometimes a niche one. It could be in technology, energy, farming or any other sector—but first understand what problem you are trying to solve”.
Farming has also taught him patience. He gives the example of coffee.
“When you plant coffee, you know it may take five years before you see results”, he said, “but you still [have to] water it every day”.
He sees entrepreneurship the same way. Building systems, communities and trust takes time. Growth may be slow at first, but daily work matters.
Adaptability is another lesson he returns to often. Farming conditions change constantly, and so do markets. In both cases, people have to keep learning, unlearning and adjusting.
“Entrepreneurship is about constantly learning new things because the world is changing all the time”, he said. “You need to stay relevant, understand what connects with [your customers] and adapt accordingly”.
Looking ahead, Tengin plans to grow its farmer network, strengthen production capacity and expand its export business. Madhu is also looking to collaborate with more platforms, storytellers and communities that can help amplify the voices behind the products.
The startup is also involved in rural community initiatives, including support for government schools and menstrual health awareness programs.
For Madhu, giving back is part of how he defines success. With more resources, he would invest further in farmer education, village-level production systems and community development.
By building a business around coconuts, Tengin is also making a larger case for rural entrepreneurship. Its work shows that a modern consumer brand can grow without losing its connection to the farmers, traditions and village ecosystems that make that growth possible. For Madhu, that is the real measure of progress: creating value that stays rooted in the community.
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A step forward that could influence how smart contracts are designed and verified.
Updated
January 8, 2026 6:32 PM

ChainGPT's robot mascot. IMAGE: CHAINGPT
A new collaboration between ChainGPT, an AI company specialising in blockchain development tools and Secret Network, a privacy-focused blockchain platform, is redefining how developers can safely build smart contracts with artificial intelligence. Together, they’ve achieved a major industry first: an AI model trained exclusively to write and audit Solidity code is now running inside a Trusted Execution Environment (TEE). For the blockchain ecosystem, this marks a turning point in how AI, privacy and on-chain development can work together.
For years, smart-contract developers have faced a trade-off. AI assistants could speed up coding and security reviews, but only if developers uploaded their most sensitive source code to external servers. That meant exposing intellectual property, confidential logic and even potential vulnerabilities. In an industry where trust is everything, this risk held many teams back from using AI at all.
ChainGPT’s Solidity-LLM aims to solve that problem. It is a specialised large language model trained on over 650,000 curated Solidity contracts, giving it a deep understanding of how real smart contracts are structured, optimised and secured. And now, by running inside SecretVM, the Confidential Virtual Machine that powers Secret Network’s encrypted compute layer, the model can assist developers without ever revealing their code to outside parties.
“Confidential computing is no longer an abstract concept,” said Luke Bowman, COO of the Secret Network Foundation. “We've shown that you can run a complex AI model, purpose-built for Solidity, inside a fully encrypted environment and that every inference can be verified on-chain. This is a real milestone for both privacy and decentralised infrastructure”.
SecretVM makes this workflow possible by using hardware-backed encryption to protect all data while computations take place. Developers don’t interact with the underlying hardware or cryptography. Instead, they simply work inside a private, sealed environment where their code stays invisible to everyone except them—even node operators. For the first time, developers can generate, test and analyse smart contracts with AI while keeping every detail confidential.
This shift opens new possibilities for the broader blockchain community. Developers gain a private coding partner that can streamline contract logic or catch vulnerabilities without risking leaks. Auditors can rely on AI-assisted analysis while keeping sensitive audit material protected. Enterprises working in finance, healthcare or governance finally have a path to adopt AI-driven blockchain automation without raising compliance concerns. Even decentralised organisations can run smart-contract agents that make decisions privately, without exposing internal logic on a public chain.
The system also supports secure model training and fine-tuning on encrypted datasets. This enables collaborative AI development without forcing anyone to share raw data—a meaningful step toward decentralised and privacy-preserving AI at scale.
By combining specialised AI with confidential computing, ChainGPT and Secret Network are shifting the trust model of on-chain development. Instead of relying on centralised cloud AI services, developers now have a verifiable, encrypted environment where they keep full control of their code, their data and their workflow. It’s a practical solution to one of blockchain’s biggest challenges: using powerful AI tools without sacrificing privacy.
As the technology evolves, the roadmap includes confidential model fine-tuning, multi-agent AI systems and cross-chain use cases. But the core advancement is already clear: developers now have a way to use AI for smart contract development that is fast, private and verifiable—without compromising the security standards that decentralised systems rely on.