DATA SCIENCE AS A SERVICE

We’re data scientists. Big data, small data, dirty, unstructured, or otherwise, we work with all of it using cutting-edge Machine Learning techniques. We aren’t just about technology either; we operate on the philosophy that real impact happens at the intersection of Statistics, Technology and Business. All of our efforts are focused towards using Data Science for tangible business outcomes, and not just sexy algorithms (though we’re great at those, too!)

We work collaboratively with our clients, to understand business problems that can be meaningfully solved with data science. Our focus is always on results - it doesn’t matter that a predictive algorithm is 99.9% accurate, if its predictions don’t help create tangible business value. To add to this, our years of experience operating in diverse sectors has also given us a lot of vertical-specific learning that we leverage to bring best-in-class solutions to our clients.

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Industries

We’ve worked with startups and enterprises across a range of industries, and we cross-pollinate learnings and best practices between them.

Healthcare

Healthcare

EMR analytics, readmission rate prediction, detecting fraudulent insurance claims, among other things. And a decade of extensive business experience in Healthcare to boot.

Retail

Retail

We’ve built algorithms to help retailers predict optimal promotion pricing, discounts, inventory and more. We’ve also built intelligent AI-powered chatbots for eCommerce businesses.

Finance

Finance

Fraud detection, enhanced credit scoring based on social data, funnel optimization, and other custom-built solutions for financial institutions.

Marketing

Marketing

We have a framework that can be used to monitor ad spends, and predict campaign outcomes to aid spend optimization. Never pay more than you have to for advertising again.

OUR SOLUTION DRIVEN APPROACH

Solution Consulting

Our Solution Consultants will closely work with the executive, business and technical stake holders of the client to craft analytical solutions.

Its a delicate balancing act between business drivers, feasibility based on data availability and modelling possibilities.

Application Development

BigData application team implements the tested Data Science Models and NLP Algorithms at scale. This team also builds applications through which the analytical solutions are consumed by the end user.

Technologies: Apache Spark, Apache Storm, Hadoop, PIG, Kafka, Hive, HBase etc.

DATA SCIENCE MODELING

Our Data Science experts design complex mathematical models and NLP techniques to implement analytical solutions.

Our tools for the trade are R, Python, NLTK, Weka etc.

Data Wrangling

Great Data Science needs ‘great’ Data. In our experience we have found upto 70% of the overall project effort goes into Data Wrangling. So we have heavily invested into tools and skills in this area.

Aquisition: Scrapping (Apache Nutch, Scrapy etc), Enterprise ETL ( Talend, Pentaho ETL, RapidMiner, Flume, Scoop etc).

Cleansing: Cleansing and normalization of acquired data using tools like Trifecta, OpenRefine etc.

Data Flow: Manage complex data flows with tools like Azkaban, Oozie, Luigi etc.

Big Data DevOPS

Our BigData DevOps team handles end to end management of the BigData infrastructure from Data Acquisition to Model Engines on on-premise or Cloud. We can roll your own infrastructure or leverage managed infrastructures like AWS EMR or Altiscale.

Services:

Automated infrastructure provisioning.

Continuous integration and delivery pipelines.

Implement and manage large clusters of Hadoop, Spark etc.

Real-time monitoring and service management.

Security consulting and implementation.

Business Use Cases

Some industries as a whole are ripe for disruption. Othes, not so much. But even there, we’ve come across business use cases for Data Science to disrupt. We’ve highlighted some of the more interesting ones here.

Call Center Analytics

Machine Learning can be used to offer real-time scripts to agents, based on sentiment analysis. Besides, caller profiles are built using call history, past complaints and other data, to route calls intelligently to the right agents, reducing Average Handle Time (AHT) by up to 40%.

IT Ops

Intelligent scoring, clustering and root-cause analysis using ML algorithms. Our solution helps automate replies, tickets and more, reducing the time to response and the probability of error, and improving efficiency.

Recruitment

It’s no secret that the passive candidates are where the real action is. Our ML models help recruitment firms identify and engage high-performing passive candidates with the right messages, to improve engagement and increase the chances of recruiting them.

SOLUTION ACCELERATORS

Many of our data science projects have similar components. A way to store data so customer privacy is protected, automated intelligent IT management, a predictive dashboard to track and forecast performance metrics. So we decided to bundle these components into plug-and-play starter kits.

Secure Data Lake

A way to store and work on data in verticals where privacy regulations are complex and demanding – Finance and Healthcare, for example. Operates on the Differential Privacy principle.

Pricing and Promotions Optimization

Retailers can use our PPO framework to quickly get an application running that saves time, money and effort when planning promotions.

Chatbot

Having built intelligent chatbots for companies across verticals, this one was a no-brainer. Use this to get a generative bot up and running in no time.

Intelligent Data Acquisition

Combines modern Natural Language Processing and Machine Learning techniques. We also recently open-sourced a Golang-based crawler that performs orders of magnitude better than other alternatives like Scrapy.

Radaptive

An ITIL-based solution for intelligent monitoring, service support and project management. Build IT monitoring applications with minimal coding effort.

Success Stories

Our data scientists have helped several companies make the jump to ML-powered excellence.

Recent Blogs

At Ideas2IT, we learn every day. From product engineering to data science, from blockchain to chatbots, our experts discuss driving forces at the intersection of tech and business. We look at business through the lens of technology, and break down how cutting-edge tech will alter the way companies in various industries operate. These are some of our learnings from working looking at mounds of data, heaps of use cases and helping businesses adopt data science in meaningful ways.

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AI, Machine Learning And Deep Learning: What Do They Mean for Businesses?

The hype surrounding Data Science buzzwords like Artificial Intelligence, Machine Learning and Deep Learning is deafening. Every business understands that they have to leverage this to stay competitive. But the way these technologies are often explained, it’s hard to understand unless you have a Ph.D.

07 DECEMBER 2017

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Social Data Science – How Menstrual Hygiene And Female Education Are Connected

Neel, the head of our Data Science practice, spent a weekend writing code to parse data from PDF files state wise that the Government releases its data in. The uncovered data points to the fact that access to better menstrual hygiene keeps girls in schools and improves female literacy.

07 SEPTEMBER 2017

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Add Machine Learning to your Android App with TensorFlow Lite

Have you ever wondered how Snapchat places that glass exactly on the bridge of your nose or that doggy nose at the tip of your nose? Human Vision makes it look like a very simple thing. All you have to do is identify your nose and place the doggy nose there. But then how simple or complex is it for a machine to identify exactly the tip of 16 million unique users and place it exactly at the tip?

06 FEBRUARY 2018

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