AgriTech & Automation
KisanKart
AI Procurement CRM & WhatsApp Automation Suite
Business Context
Agricultural procurement operates on extremely tight timelines. KisanKart was losing deals because manual tracking across WhatsApp and spreadsheets caused delays in responding to mandi buyers.
The core problem — Create a centralized system that instantly captures, translates, categorizes, and routes procurement requests from WhatsApp to the correct field agent, without disrupting the buyers existing communication habits.
Architecture
Constraints
Buyers operate entirely on WhatsApp. They use mixed languages and voice notes. Internet connectivity for field agents is often poor, requiring an extremely lightweight frontend.
System Design
We decoupled the ingestion engine from the CRM UI. A Node.js microservice listens to WhatsApp Business API webhooks, streaming messages to an AI parsing layer. The AI extracts intent, crop type, quantity, and urgency, inserting structured records into Postgres. Websockets then push real-time alerts to the agent dashboard.
Implementation Details
We implemented an optimistic UI for the agent dashboard to ensure it felt responsive even on 3G connections. Background cron jobs continuously monitor lead staleness, automatically triggering follow-up WhatsApp templates if an agent hasn't responded within 15 minutes.
Tech Stack & Rationale
Node.js & Express
Provided a lightweight, non-blocking backend critical for handling high volumes of concurrent WhatsApp webhooks during peak trading hours.
PostgreSQL
Ensured ACID compliance for financial quotes and inventory logs, which cannot afford eventual consistency.
OpenAI API
Used to parse unstructured multilingual WhatsApp messages (Hindi/Punjabi/English) into structured JSON lead data.
Outcomes
Lead response times dropped from hours to under 3 minutes. The system processes thousands of unstructured messages daily, automatically qualifying high-value bulk buyers and assigning them to senior agents.
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