PInCER addresses the emerging need of the agriculture sector arising from the rapid growth of institutional financing through crop loans and crop risk financing (insurance), which requires comprehensive and well-organized data and analytics.

We carry out the farm and village-level crop acreage, health, and yield forecast and estimations using remote sensing, advanced modeling, artificial intelligence, and machine learning. This, combined with other datasets, supports timely distress mitigation, village prioritization for better prospecting, farmer credit rating, better portfolio risk management for lenders and insurers, early insurance claim settlement, high-resolution crop monitoring, efficient communication with farmers, and early claim settlement.

How does PInCER help?

PInCER is a SaaS-based portal that provides government and agri-sectors, crop acreage, and yield estimates faster, more accurately, and at higher resolution, using satellite, drone, and AI/ML technologies. These estimates input into sector-specific applications including precision farming, farm credit rating, digital exchange and price discovery. PInCER platform helps to derive remote-sensing based crop-wise estimate of acreage and yield of the area under cultivation for districts/blocks/villages/farms.

PInCER Modules Enable the Insurance Industry

Weather and Crop Yield Outlook

Get country, state or district-wise yield and acreage outlook and estimation for all major crops

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Portfolio Analysis & Premium Calculator

Arrive at premium pricing to bid for various clusters and adopt a suitable reinsurance strategy

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In-season Tracking

Track crop growth during the season to get early heads-up on distress hotspots and estimate likely output

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Farmer Risk Profile Verification

Verify crop insurance policies to assess the probability of a moral hazard, and manage faster claim settlement

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Farmer decision support system

An integrated web and mobile app platform that allows geo-coding and two-way communication with farmers

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Key benefits of using PINCER

Satellite and weather-based advisory

Prioritize your target area

Demand forecasting & effective go-to-market strategies

Better manpower & resource allocation

Track crop-specific acreage and yield estimation

Target field visits for your last-mile delivery

Success Stories

Mapping maize crop acreage for an agrochemical and agricultural biotechnology corporation

The client wanted to conduct a study to estimate and map the crop acreage of Maize across 5 countries in Asia (China, India, Pakistan, Philippines, Thailand & Vietnam). The aim was to have a scalable approach to identify Maize-growing regions in these countries and estimate crop acreage, which will eventually help the company plan for its maize-oriented products. 

We adopted an integrated approach to use satellite imagery, ground survey, and secondary information to develop an understanding of Maize crop acreage. We conducted a detailed analysis to understand the Maize crop’s sowing window, crop duration, and spatial distribution/spread across the five Asian countries during 2018-19’s multiple cropping seasons.


The client wanted to conduct a pilot project to compare the potential scope, applicability, and viability of various advanced technology-based yield estimations for three crops – Paddy, Cotton, and Red Gram – grown in different agro-climatological zones of India.

We proposed an approach where robust machine algorithms were clubbed with efficient remote sensing technologies and physical surveys. It captured ground control points (GCPs) critical for capturing location, crop signature, and CCE data.  We generated crop spread maps for specific crops using high spatial resolution satellite imageries.

Assessing crop growth using remote-sensing techniques for a non-profit international research institute

The client wanted to conduct a study for crop health monitoring, pre-harvest crop acreage, and yield estimation to find out the potential scope, applicability, and viability of scientific and modern techniques in agricultural assessments. The areas of study were four soybean-growing districts of Maharashtra (i.e., Kolhapur, Latur, Osmanabad, and Washim). 

We conducted an experimental study to compare the potential scope, applicability, and viability of four advanced technology-based agricultural assessment techniques for soybean as a test crop with different Agro-climatological set-ups in Kharif 2016.

Crop yield estimation & supply chain management for an Apex-Export Trade Promotion Active government entity

The client wanted to assess the Basmati crop acreage in northern India to estimate yield, thereby assisting in effectively managing the Basmati supply chain in India, mainly for exports.

We adopted an integrated approach to use satellite remote sensing, ground survey, and secondary information to develop an understanding of Basmati acreage. It was followed by satellite image processing to estimate the spatial distribution and distinction of different rice varieties from Basmati, depending on the various crop growth stages at the time of imagery acquisition.

Brochure | Insurance Industry

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