Humans enjoy cognitive ability to think at speed,
predict trends & make meaningful decisions.
At Imaginea, we build solutions that think,
analyze & predict the way humans do.



In this webinar, we explained the application of Spark’s machine learning pipeline for predicting Click Through Rates (CTRs). We also covered the many challenges you may face & how to overcome them.


Big Data analytics coupled with machine learning is opening up new possibilities to build analytical systems that can learn & evolve like humans.

Imagine the possibility of predicting breast cancer based on mammography scans of women, stock market behavior on a given day, or a possible high value purchase from a customer.

At Imaginea, we help companies leverage the power of Big Data analytics using Apache Spark. We are one of the early Apache Spark adopters, and have been successfully developing commercial grade Spark solutions since 2014. We have niche capabilities in Next Product To Buy algorithms, Deep Learning techniques, Machine Learning algorithms and Natural Language Processing.


Constantly learn from data to forecast behaviour

Being able to predict the customer intent can help personalize the buying experience. The predictive recommendation module we built for a leading retail personalization suite increased the average customer order value by 45%.


Identify patterns &
spot the outliers

Identifying fraudulent events shields you from business risks. For an Integrated Health Benefit Platform, we built a solution that identifies patterns and flags possible fraudulent claims.


Semantic search using Natural Language Processing

A contextual understanding makes the search more meaningful. We built a dynamic non textual code search engine that quickly scans over 1 billion lines of code in
Github projects to find the most idiomatic code references
for developers.

Experience the power of Apache Spark with Imaginea

Why Apache Spark with Imaginea?

Among top contributor to Spark code

Imaginea is among the top contributor to the Spark code. We have been contributing to the code since 2013 when it was a UC Berkley project. Our notable contribution includes Spark Scala upgradation, TaskContext API, Compilation for Scala 2.11, Spark UI, Doc Generation & more.

Building products on Spark since 2014

We are one of the very few early stage Spark adopters. We started using Spark to build commercial grade solutions since 2014. For instance, our contextual code search platform KodeBeagle which leverages the power of Big Data analytics was built using Spark.

Visit KodeBeagle >>

Contribution to Big Data opensource projects

Imaginea is committed to building a strong Big Data opensource ecosystem. We are active contributors to Apache Hadoop and Zeppelin code. Notable contribution includes over 20 patches to Apache Hadoop and contribution in the areas such as JDBC Intepreter, Wildcard Parsing, Integration to Zeppelin.

Get in touch for a PoC