Feature-

● Collect farm and farmer data

● Sources: Ground team surveys, Government farmer databases, Call centre calls, Mobile

app and Web portal

● Call and Online Analytics on Crop sowing pattern, Crop diseases, Market

sales, Product sales

● Run targeted SMS and Push Geo-location campaigns for fertilizers,

pesticides, seeds, produce buy-back

● Machine Learning: Run supervised learning over satellite imagery to perform crop yield prediction

Big Data Analytics Stack

● Airflow, Argo
● Sqoop, Kafka, Spark
● HDFS, Minio, SeaweedFS
● Hive
● Mongodb, Cassandra, Aerospike, ElasticSearch, PrestoDB, Druid
● Kubernetes, Docker
● Superset, Metabase
● PowerBI, Tableau

Machine Learning

● Descriptive and Predictive analysis of structured data - Risk analysis, Fraud detection,
Security incident detection
● Computer vision - Object detection based signature detection in scanned documents.
Image-based document classification and extraction, License-plate detection
● NLP - Named entity recognition, Sequence to Sequence modelling, Sentiment analysis,
Text-based classification

Technology Stack

● TensorFlow, KubeFlow, PyTorch, AutoML, MLlib, Dask, Cloud ML, BERT
● Amazon, Google, Microsoft, Linode, Paperspace