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How we created impact on the life of shrimp farmers by incorporating cutting edge technologies. Business Situation Keeping farmer first the client wanted to have a model and strategy driven by big data and technology focused on delivering environmentally sound, sustainable and profitable farming solutions. GrowYT Approach Increased the flow of information, data driven study and strategy were prepared. Digitised the aquaculture system while strongly focusing on solving real problems rather than perceived problems. Integrated farmers wisdom with futuristic technology and provided them real time solutions to optimally utilize their resources, increase productivity and minimize losses. Prepared AI-ML based models to provide microclimatic forecasts and accurate price and demand forecasts. Infused state of the art Hyperspectral Imaging technologies to early detect diseases and stages of shrimps. We developed go to market strategy driven by futuristic technology and Data & Analytics solutions. Developed the smooth multilingual mobile application integrating all the above features bringing world to the tip of fingers. Engagement Created a fair sustainable digital ecosystem by ensuring best prices and transparent payments for shrimp harvest, benefitting all stakeholders. Developed a strong feedback mechanism and ensured real time solution to all through live customer support mechanism. Benefits & Outcomes Provided farmers with recommendations and assistance from aquaculture experts for optimal shrimp harvesting. Enabled rational decision making by farmers enhancing yield, efficiency and profit. Created a technology driven transparent ecosystem improving market linkage certainty and increasing value realisation for the farmers. Key Takeaways Using advances in technology, GrowYT builds a systematic value chain for shrimp farming businesses, resulting in an integrated and sustainable ecosystem to strengthen global food security in the future. Close

How we enabled a leading loan provider to do customer segmentation and minimize documentation errors. Business Situation The client wanted to have a model to identify post loan behavior of defaulters, a credit risk assessment model for better decision making, and solution to minimize documentation errors. GrowYT Approach We built a team of sector data scientists and data analysts to create insight generation and develop ML & AI based models. We designed and implemented ML based hybrid early warning model predicting EMI default- post loan disbursal. We designed ML based hybrid customer credit risk assessment model – pre loan disbursal. Designed Deep Learning Algorithms for Selfie and Photo match based on facial landmarks. Designed and Deployed Name fuzzy match algorithm. Engagement We generated valuable insights based on above models and did segmentation of customer base and evaluated risk associated with each segment. Benefits & Outcomes Identified distress customers early on which supported client’s collection team. Enabled client to forecast possible loss projections. Automated majority of underwriting process which helped credit underwriters in rational decision making and increased their work efficiency. Algorithms minimized errors in name matching and face recognition to greater extent. Key Takeaways Models and algorithms to be evolved with changing human behavior. Events like COVID Pandemic corrupts the data making it futile.  

How we enabled a leading retail super store chain to enhance sales and revenue using AI based solutions. Business Situation The client wanted to have a model to optimize cost price of stock, rationalize assortment of items and have better demand forecasting. GrowYT Approach We integrated salesforce, promotion campaign, customer feedback, google analytics and other store data on a cloud-based data warehouse. We developed pricing optimization tool for Stock Keeping Units. Found key central items using state of the art algorithms and designed basketing or promotions around those items. Used RFM model and Bayesian Models to find customer lifetime value (CLTV). Designed Algorithms to forecast Visitor count at store to optimize resources. Engagement We generated valuable insights based on above models to drive item assortment. We used above models to achieve customer lifetime value which is unique to each store. Benefits & Outcomes Enabled marketing team planning promotions. Provided advance forecasts for optimal allocation of labour at all the retail stores. Enabled stores to retain old customers and increase new customer base. Optimized item stock based on demand and visitor forecasting. Key Takeaways We enabled all the retail stores to measure their performance as well as take insight-based action to improve sales, revenue and profit. Hypothesis based data sanity is indispensable to cater dynamic human behavior.