🌾 Farm Sutra — AI-Powered Farming Assistant for Rural India
💡 Inspiration
India has over 140 million farmers, yet most of them make critical decisions — when to sell, what disease is attacking their crop, whether to take a loan — based on word of mouth or outdated information.
The breaking point for us was a simple observation: a farmer in rural Haryana loses 30–40% of his crop yield every season not because he lacks hard work, but because he lacks access — access to timely market prices, access to expert crop diagnosis, access to fair credit.
Existing agri-apps are built for smartphone-savvy users in English. They ignore the reality that most Indian farmers:
- Speak Hindi, Punjabi, Tamil, or Haryanvi — not English
- Are on 2G networks with limited data
- Have no formal credit history, making banks turn them away
We asked ourselves: What if AI could sit in every farmer's pocket — speaking his language, understanding his crop, helping him sell at the right price?
That question became Farm Sutra.
🛠️ How We Built It
Farm Sutra is a full-stack mobile + cloud application built on the AWS ecosystem, powered at its core by Amazon Nova Pro via Amazon Bedrock.
Architecture Overview
React Native (Expo) App
│
├── AWS Amplify (API Gateway + Auth layer)
│ │
│ └── AWS Lambda (Node.js)
│ │
│ └── Amazon Bedrock
│ │
│ └── Amazon Nova Pro v1
│
├── Open-Meteo API (Live GPS Weather)
└── AsyncStorage (Offline chat persistence)
Feature Breakdown
🤖 Farm Sutra AI (ChatBot)
The AI chatbot uses Amazon Nova Pro via Bedrock for all responses. Every query is augmented with a language instruction so Nova replies strictly in the farmer's chosen language — Hindi, Punjabi, Tamil, Haryanvi, or English.
Crop Scanner — the most technically complex feature — sends both a base64-encoded image and a fully translated prompt to Nova's multimodal endpoint. The prompt itself is written in the farmer's language, structured to extract disease name, treatment plan, urgency, and confidence level.
$$\text{Crop Health Score} = f(\text{Image}{\text{base64}}, \text{Prompt}{\text{lang}}, \text{Nova Pro Multimodal})$$
🛒 Mandi (Market)
A real-time marketplace where farmers list their crops and buyers post demand. Built with AsyncStorage for persistence and includes live GPS-based weather context at the top of the screen.
🌦️ AgriWeather
Uses Open-Meteo's free GPS API to pull 7-day live forecasts. The AI layer converts raw WMO weather codes into actionable farming advice — "High humidity for 2 days — fungal infection risk for your wheat".
🏦 Credit Score
A proprietary farmer credit scoring system that rewards positive farming behaviors — scanning crops, checking weather, selling in the Mandi. This creates a verifiable activity log for farmers who have zero formal credit history.
$$\text{Credit Score} = \text{Base Score} + \sum_{i=1}^{n} \text{ActivityPoints}_i$$
Where each activity (crop scan, weather check, market listing) contributes weighted points to build a farmer's financial credibility over time.
🌍 Multilingual Engine
Every single string in the app — UI labels, AI prompts, error messages, weather alerts, pest warnings — is translated into 5 languages:
| Language | Region |
|---|---|
| English | Default |
| Hindi (हिन्दी) | North India |
| Punjabi (ਪੰਜਾਬੀ) | Punjab |
| Haryanvi (हरियाणवी) | Haryana |
| Tamil (தமிழ்) | South India |
📚 What We Learned
Prompt engineering is everything for multilingual AI. Simply asking Nova to "reply in Hindi" wasn't enough — we had to write the entire system prompt in the target language to get culturally accurate, dialect-appropriate responses. The Haryanvi dialect prompt took multiple iterations.
Multimodal inputs require careful image compression. Sending full-resolution images to Bedrock on a 2G network was impractical. We settled on
quality: 0.5in Expo ImagePicker — enough for accurate disease diagnosis while staying 2G-friendly.Offline UX is a feature, not an afterthought. For rural farmers, connectivity is unreliable. Building graceful offline handling — persistent chat history, informative banners, queue messaging — required as much thought as the AI integration itself.
Credit scoring for the unbanked is a design challenge. Traditional credit models require financial history. We learned to think differently — behavior as credit — rewarding consistent, verifiable farming activities instead.
🚧 Challenges We Faced
1. Haryanvi Dialect
Haryanvi is not a standard language with NLP support. Getting Amazon Nova to respond in authentic Haryanvi farmer dialect — with words like "सै", "कोन्या", "आपणा" — required hand-crafting every prompt and testing with native speakers. No existing dataset or library helped here.
2. 2G Network Optimization
Most agri-apps assume 4G. We had to rethink every API call:
- Image compression before Bedrock upload
- AsyncStorage chat persistence to avoid re-fetching
- Open-Meteo chosen specifically for its lightweight JSON response
3. Multimodal Prompt Translation
Writing the crop scan diagnostic prompt in 5 languages — with the exact same structured output format (emojis as anchors: 🌿, 🔍, 🦠, 💊, ⏰) — so that parsing remains consistent regardless of language was a significant challenge.
4. Credit Score Without Financial Data
Building a meaningful credit scoring system for farmers who have zero bank history meant inventing new signals. We used in-app behavioral data as a proxy for creditworthiness — a concept we're proud of and believe has real-world applicability.
🔮 What's Next for Farm Sutra
- Amazon Nova 2 Sonic integration — Replace mock voice input with real multilingual speech-to-speech using Nova 2 Sonic, enabling truly voice-first interaction for low-literacy farmers
- Nova 2 Omni — Video-based crop scanning, where farmers can record a 10-second video of their field for richer disease detection
- Bank API integration — Connect the Credit Score tab directly to Kisan Credit Card loan applications
- Government scheme push— Partner with state agriculture departments to deliver PM-KISAN and soil health scheme notifications directly to farmers
"Farm Sutra is not just an app. It's a voice for the farmer who never had one."
Built With
- amazon-web-services
- amplify
- apigateway
- asyncstorage
- bedrock
- expo.io
- lambda
- novapro
- openmeteo
- react-native
- typescript
- vercel
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