Drishti

Project Name: DRISHTI Tagline: Predicting agricultural supply chain disruptions before they reach the farmer. The Problem We Solve Global agriculture is highly vulnerable to sudden geopolitical shocks—such as wars, trade embargoes, port closures, and extreme weather events. When these global disruptions occur, they cause massive fluctuations in commodity prices and supply chain bottlenecks. Unfortunately, farmers and local policymakers are often the last to know. By the time global news translates into local market impact, farmers have already suffered severe financial losses, misallocated their resources, or faced crop spoilage. Furthermore, a massive language and technology barrier prevents rural farmers from accessing advanced early warnings or expert agronomic intelligence. There is a critical disconnect between high-level macroeconomic data and ground-level farmer action. What is DRISHTI? (Project Description) DRISHTI is a multimodal, AI-powered Early Warning System designed to shield agricultural supply chains from global instability. By unifying deterministic Machine Learning forecasting with the advanced reasoning of Google Gemini AI, DRISHTI acts as a real-time bridge between global geopolitical conflicts and localized farmer advisories. It continuously monitors the globe for supply chain threats and instantly translates those threats into actionable, regional-language guidance for farmers. How It Works (Multi-Agent Architecture): To process complex global data in real-time, DRISHTI utilizes a sophisticated orchestration of specialized AI agents powered by the Gemini Interactions API: The Orchestrator Agent: Acts as the central nervous system of the platform, routing requests between specialized sub-agents and ensuring seamless communication between the ML backend and the Next.js frontend. Event Processor & Impact Reasoner Agents: These agents continuously scrape global news sources. Utilizing Gemini 3.5 Flash, the Event Processor performs high-speed extraction of geopolitical entities and sentiment analysis. The Impact Reasoner then analyzes this data to identify direct threats to agricultural trade routes. Risk Predictor Agent (ML Pipeline): This agent bridges generative AI with deterministic Machine Learning. It feeds the extracted geopolitical data into our Python backend, where scikit-learn and XGBoost models cross-reference the events with historical trade datasets to calculate a real-time Crop Risk Index and localized "Farmer Risk Scores". Advisory Generator & Multimodal Agents: To bridge the technology gap, these agents power our voice-enabled Farmer Assistant using Gemini Omni. They translate agronomic queries from 10+ regional Indian languages in real-time, generate expert agricultural advice based on the calculated risk scores, and utilize Nano Banana 2 Lite to provide instant computer vision for crop disease detection from uploaded images. The Result: What used to take weeks of market analysis now takes seconds. DRISHTI empowers policymakers to secure supply chains and equips farmers with the localized intelligence they need to protect their livelihoods before disaster strikes.