The Operating System for
Modern Agriculture.

Bridging the Global
Implementation Gap

Precision agriculture isn't a concept—it's a deployed reality. We surveyed the most advanced enterprise farm systems across Europe and America and engineered COCO to deliver the same ruthless intelligence for Indian agronomy.

THE MACOJAL ENGINE

Uncompromised
Architecture.

Scroll to unpack the stack.

Neural Processing

Edge AI compute nodes execute localized models.

Data Lake

Peta-scale ingestion of historic and live IoT telemetry.

ML Abstraction

PyTorch ensemble models dynamically adjusting to constraints.

Zero-Trust Security

Military-grade encryption securing all farm-level IP.

PREDICTIVE MODELING

Algorithmically Guaranteed
Harvest Outcomes.

Eliminate guesswork. Our proprietary machine learning layers forecast yield density and climatic risks with unparalleled enterprise accuracy.

Yield Accuracy

0%

Consistently outperforming traditional agronomist manual sampling methods through deep satellite integration.

Growth Multiplier

0X

Data Points Analyzed

0M+

Daily ingestion of multi-spectral, thermal, and SAR radar data points per individual farming cluster globally.

REAL WORLD DEPLOYMENT

Precision Agronomy,
Not Just Dashboards.

COCO goes beyond simple weather tracking. We provide actionable, field-level agronomic intelligence designed for Agronomists and FPO leadership to make high-stakes operational decisions.

01

Pre-symptomatic Stress Detection

COCO's vision models analyze multi-spectral satellite imagery to detect chlorophyll degradation and water stress up to 14 days before visible symptoms appear on the crop canopy, allowing proactive intervention.

14 Days
Advanced Warning
02

Variable Rate Nitrogen Mapping

Stop carpet-bombing fertilizer. We generate hyper-local Nitrogen application maps per acre based on historic yield zones and current vegetative indices, reducing fertilizer costs by 20% while protecting soil health.

20%
Cost Reduction
03

Micro-Climate Irrigation Scheduling

Integrating IMD telemetry with local soil-moisture models, COCO predicts the exact evapotranspiration (ETc) drop per field. It alerts FPOs exactly when and how much to irrigate, saving critical water resources.

35%
Water Saved
04

Autonomous Fleet Orchestration

For mechanized FPOs, COCO optimizes tractor routing and harvester deployment based on maturity indices across thousands of acres, minimizing idle fuel burn and maximizing daily harvest coverage.

12%
Fuel Efficiency
DATA PIPELINE

Orbit to Field in
Under 100 Milliseconds.

A transparent look at how raw planetary data is transformed into immediate agricultural intelligence. Built for absolute zero-latency.

Phase 01

Data Acquisition

Multispectral imagery from ESA Sentinel-2 is ingested every 3-5 days. Simultaneously, local IoT weather stations transmit micro-climate ground truth telemetry via LoRaWAN.

Phase 02

Edge Pre-Processing

Raw data is cleaned immediately. Cloud cover interference is algorithmically removed using near-infrared (NIR) data, ensuring pristine inputs for the ML layers.

Phase 03

Inference & Normalization

Our proprietary PyTorch models compute NDVI, NDRE, and MSAVI indices. Yield forecast engines run localized XGBoost models mapped against our 10-year historical PostgreSQL lake.

Phase 04

Actionable Intelligence

FPO managers and Agronomists receive immediate, hyper-localized alerts on their dashboard. From heat-wave warnings to specific pest-probability heatmaps per acre.

Core Technical Modules

5 Pillars of COCO
Crop Intelligence

Crop Health Studio

Module 01

Satellite NDVI Viewer

Ingesting ESA Sentinel-2 feeds, COCO computes field-level Normalized Difference Vegetation Index (NDVI). Detect crop stress before it's visible to the naked eye with automated multi-resolution change detection.

Green: HealthyYellow: Impending StressRed: Critical Intervention Needed

Edge AI Diagnosis

Module 02

Mobile Image Diagnosis

A localized computer vision pipeline. Agronomists photograph affected leaves; COCO instantly references proprietary models fine-tuned on indigenous pest and malady strains—bypassing generic US/EU parameters.

Leaf BlightPowdery MildewNutrient Deficiency Recognition

Yield Multiplier

Module 03

Smart Crop Engine

An intelligent recommendation matrix referencing district-level soil data, climate bands, and historical yield constraints to advise exact sowing windows and optimal crop selections.

Profit Band EstimationsCrop Rotation ModelingYield Maximization

Market Intelligence

Module 04

Mandi Price Forecast

We don't just report current prices. Using ensemble ML forecasting natively integrated with Agmarknet datasets, COCO predicts 15-30 day price movements to optimize harvest and logistics timelines.

Predictive Trend LinesBest-Sell Location MatchingLogistical Optimization

Actionable Alerts

Module 05

Weather Risk Matrix

Connecting local IMD data to crop-specific vulnerability thresholds. COCO doesn't just say 'it will rain'; it instructs 'delay fertilizer application for 24 hours'.

Frost & Heat StressPesticide Washout PreventionHyper-local Forecasting
TECHNICAL INFRASTRUCTURE

Built for FPO
and Government Scale

COCO isn't a lightweight farmer app. It's a high-throughput, multi-tenant Intelligence API and Dashboard built on Kubernetes, PostgreSQL, and FastAPI.