Nepal's farmers grow 70% of the country's food. Two-thirds of Nepal works the land. Most of them are one bad season from crisis. We're here to change that.
10,000 Farms is building a farmer-first, knowledge-led, digital-first resilience model for Nepal's smallholder farmers — trusted, timely, local-language decision support for the crop-cycle moments that matter most.
A farmer-first resilience approach for Nepal
10,000 Farms begins with a practical belief: smallholder farmers need trusted, timely, local-language knowledge that helps them make better decisions before, during, and after the crop cycle.
The program is knowledge-led and digital-first, but not digital-only. Digital tools reduce the cost of reaching farmers; local validation, field relationships, and trusted messengers drive adoption.
Every piece of guidance is built around real farmer decisions — not what the literature says, not what donors want to hear.
Short, visual, local-language learning designed around the moments in the crop cycle that actually change outcomes.
Digital tools reduce cost. Local relationships drive adoption. We need both.
The gap isn't effort. It's what farmers know.
Nepal's 2.7 million smallholder farm households produce 70% of the country's food on plots averaging 0.6 hectares. Barely enough to feed a family. Not enough to build a future.
Nearly 72% borrow from informal moneylenders. Climate shocks are getting worse. And Nepal now imports 18% of its total merchandise bill in food, while the farmers growing it lack the basic decision support to improve their yields, reduce their losses, or reach a buyer.
The gap isn't effort. It isn't land. It's knowledge. Trusted, timely, in the right language, at the right moment in the crop cycle.
The average Nepali farm is 0.6 hectares. Large enough to survive on. Too small to scale, negotiate, or mechanize.
Most farmers rely on informal sources — neighbors, traders, word of mouth — for decisions that determine their entire season.
Knowing what to do isn't enough. Without access to inputs, storage, transport, and buyers, the right decision still leads nowhere.
Floods, drought, and landslides are becoming more frequent. For a smallholder, one bad season isn't a setback — it's a debt spiral.
The central challenge is the gap between knowing, doing, and earning.
Low cost to reach. High trust to act.
The goal was never to build the most advanced platform. It was to find the lowest-cost channel that farmers can actually access, trust, and do something with.
Digital tools get us there cheaply. Local relationships make it stick. The model is built around both.
- 01Listen
Start with the farmer's reality — what crop, what risk, what market, what phone, what language.
- 02Translate
Turn technical knowledge into short, visual, local-language guidance built for the moments that matter most.
- 03Test
Put it in front of real farmers. Do they understand it? Do they trust it? Can they act on it?
- 04Support
Connect the guidance to partners, local experts, and practical next steps — not just information.
- 05Iterate
Fix what doesn't work. Cut what doesn't land. Scale what does.
"She pointed to her phone. YouTube. No program. No extension worker. Just access."
The phone is already in their pocket.
Nepal's mobile connections now exceed its population. Internet penetration is large enough to support digital guidance at meaningful scale. The infrastructure exists. What's missing is content that's actually built for the people using it.
That's why the model includes offline and human-reinforced pathways too — through local partners, field relationships, and trusted messengers. Because some farmers aren't connected yet. And for them, the person they trust most is still the one standing next to them.
We're building this carefully. Here's what that looks like.
Phase 1 is not a pilot. It's the work that makes a pilot responsible.
Before we put anything in front of a farmer, we need to know the knowledge architecture is sound, the content is trustworthy, the measurement is honest, and the partners are real. That's what we're doing now.
What does the literature actually say about what works for smallholder farmers in Nepal? We start there.
Who's already in the field? Universities, cooperatives, extension workers, supplier networks, farmer groups. We map before we build.
Where in the crop cycle does the right guidance change an outcome? We identify those moments precisely.
Short, visual, local-language modules for an initial vegetable value chain — designed around real decisions, not generic content.
How will we know if it's working? We design the measurement system before Phase 2 begins, not after.
Incremental net farm margin per cultivated acre attributable to sustained adoption of validated practices, measured net of program delivery costs.
10,000 households. We start by earning the first ones.
The number is the north star, not the starting line. We won't claim farmers we haven't reached or impact we haven't measured. Progress here will update only when farmer participation is formally validated through the pilot and scale phases that follow.
That's the commitment.
- Current validated reach0 farm households
- Long-term target10,000 farm households
- StatusPhase 1
Readiness milestones — not farmer reach.
- Evidence synthesisIn progress
- Ecosystem mappingIn progress
- Content architectureIn progress
- Partner blueprintIn progress
- Measurement designIn progress
Built for how farmers actually learn
10,000 Farms is building a local-language learning system for practical crop-cycle decisions. This section will eventually host short video tutorials, visual guides, and learning modules designed for farmers and field partners.
Video tutorials and farmer-facing learning modules will live here.
Coming soon — short, practical learning modules for farmer decision support.
Coming SoonWe're designing the learning system before producing the content, so every module maps to a real decision farmers face in the crop cycle.
An open knowledge layer for understanding Nepal.
10,000 Farms aims to build more than farmer-facing guidance. Over time, we also want to create a public-facing data center that helps anyone understand key agricultural and environmental conditions across Nepal.
This future section may include temperature, water, rainfall, air, soil, and other ground-level context that shapes how farmers plan, adapt, and respond. The goal is to make useful Nepal-focused data more visible, more accessible, and easier to understand.
Seasonal and regional temperature signals across Nepal's agricultural zones.
Surface water, irrigation availability, and basin-level conditions.
Monsoon timing, intensity, and moisture patterns relevant to crop cycles.
Air conditions and atmospheric context that affect rural and farming communities.
Soil health, terrain, and ground-level conditions across Nepal's diverse landscape.
Cropping context, productivity signals, and on-the-ground agricultural indicators.
A small team. Built around field reality.
Studied field-led design for smallholder systems. Built BI solutions and GTM from zero to scale, forging ventures with leading financial institutions across complex regulatory environments.
In Nepal, a farmer showed Tashi she had learned to grow tomatoes from YouTube — no program, no extension worker. Inspired by Khan Academy's conviction that knowledge can reach anyone at scale, that observation became the founding logic of 10,000 Farms.
Besides 10,000 Farms, Tashi is a 15-year veteran of building partnerships and GTM programs at a BI firm whose clients span global banks, insurers, and SMEs. Enterprise sales at Apple. Speaks four languages.
B.S., New York University. Master's in Global Development, Cornell University, magna cum laude.
Outside of work, an avid runner, swimmer, and alpinist — and a volunteer with NYC Parks and the Vipassana community.
B.S. in Business Data Analytics and International Business Studies. Background in strategy, analytics, and research-led problem solving across operations, business intelligence, and early-stage initiatives.
For Siddharth, 10,000 Farms connects strategy, analytics, and impact with a simple belief: useful knowledge should not stay locked inside institutions, reports, or expert networks. Farmers should be able to access practical, trusted guidance at the moment a decision actually matters.
His work on 10,000 Farms focuses on research, program structure, analytics, partner readiness, and turning complex agricultural and development ideas into clear systems that can be tested responsibly.
Siddharth holds a B.S. in Business Data Analytics with International Business Studies from Arizona State University and also studied at the University of Leeds. His background spans strategy, business analytics, operations, business intelligence, and early-stage initiative development. He is also a Cornell Future Leaders MBA admit through the deferred MBA pathway.
Outside of work, Siddharth is interested in running, trekking, sports, and building ideas that sit at the intersection of technology, strategy, and real-world problem solving.
Former Clinical Research Physician, University of Zürich, Long Covid. Led medical training at Kakuma Refugee Camp, Kenya. Partnered with Geneva InZone & UNHCR.
My entire career in medicine and public health comes down to one fact: health starts with food. You can't build resilient communities when people are one bad harvest from a crisis.
I believe the most effective interventions don't hand out supplies — they transfer knowledge. What works in the field has to be practical, local, and something a farmer can act on today. That's what drew me to 10,000 Farms.
This isn't just an agriculture initiative. It's equipping people with the understanding they need to secure their own livelihoods on their own terms.
Publications & Research
Publications and research notes will be added here as the 10,000 Farms Phase 1 research work develops.
Stay updated as we build the Phase 1 proof of concept and develop future partner opportunities.
Visit LinkedInClear answers about the current stage, model, and partner opportunity
An early-stage agricultural resilience initiative for Nepal's smallholder farmers, designed to build trusted, timely, local-language knowledge systems that help farmers make better decisions across the crop cycle.
Phase 1. We're validating the model — the knowledge architecture, the farmer decision journey, the content approach, the partner network, and the measurement system — before we run a pilot. The 10,000-household target is the long-term ambition. We'll earn it one validated step at a time.
Many smallholder farmers face a gap between knowing, doing, and earning. Practical, trusted, local-language guidance can improve decision quality — but only when it is tied to real farmer constraints, local trust, and feasible action.
No. Digital-first, not digital-only. Digital tools reduce cost and improve reach; local validation, field relationships, and trusted messengers drive adoption.
Vegetables are income-sensitive and vulnerable to postharvest loss, which makes them a strong starting point for testing whether better guidance can improve farmer decision-making and future net-margin outcomes.
Universities, faculty advisors, student teams, agronomic experts, field partners, research collaborators, and funders who can help pressure-test the model before the pilot.
Agronomic content review, literature review, farmer journey mapping, measurement design, local-language learning modules, field connections, and responsible pilot planning.
The long-term North Star metric is incremental net farm margin per cultivated acre attributable to sustained adoption of validated practices, measured net of program delivery costs.
Institutions and collaborators helping shape the 10,000 Farms journey.
Additional university, research, and field partners will be listed here as Phase 1 collaborations are formalized.
The model is ready to be stress-tested. That's where you come in.
We're not looking for endorsements. We're looking for people who will push back, pressure-test the assumptions, and help us get it right before we scale.
That means agronomists who can tell us where the content is wrong. Researchers who can sharpen the measurement. Field partners who know what actually works in a Nepali village. And funders who understand that responsible impact starts before the pilot, not after.
If that's you — let's talk.
- Review agronomic content for technical accuracy and local applicability.
- Support literature review, farmer journey mapping, and intervention design.
- Help design measurement for adoption, trust, cost per adoption, and net-margin outcomes.
- Contribute to short, practical, local-language learning modules and visual guides.
- Connect the team to field partners, extension actors, or research collaborators.
We aim to respond within 3 days.