Artificial Intelligence / Machine Learning

Applications of AI / ML

With exponential rise in business data and increase in computing power, decades old fields of Artificial Intelligence and Machine learning are now becoming increasingly relevant. We work with clients in leveraging their data to develop machine learning models that enable intelligent decision making and empower machines to conduct intelligent tasks.

  • Image / Object recognition – Recognizing or analyzing images or objects from still pictures or videos – be it customers in a mall or goods in a warehouse or crop in farms – is often a tedious task when done manually. AI or Deep learning backed algorithm can help recognize and analyze thousands of images and assist managers in monitoring business or make intelligent decisions.
  • Customer segmentation – Mining customer data to understand different customer categories that exist. Often, segments which aren’t visible through human analysis or intuition is brought forward through unsupervised modelling techniques
  • Recommendation engine – Using the customer history of buying and search pattern, generate recommendations for best suited products and services for customers, thus improving the sales opportunities
  • Demand forecasting – Demand forecasting is critical for efficient supply chain. We leverage Machine learning techniques by using statistical algorithms to decipher demand patterns (e.g. seasonality, peaks) and establish interrelationship between demand and factors like weather, customer demographics, category growth, events, population growth and health of economy.
  • Sentiment analysis – Organizations get to hear their customers’ feedback at their websites, on social media or at contact centers. We help customers analyze customer feedback and identify customers’ sentiments using NLP techniques.

Case Studies

What We Do

Big Data implementation

We can help you in feasibility check, implementing Big Data technology customized as per your use case and defining business problem in clear and concise way.

Dashboards / BI

Assist in creating Dashboards and customized business reports on a single click.

Technologies

Statistical modeling

Apply advanced statistical principles and techniques like time series and regression to build machine learning and artificial intelligence models.

Supervised learning / unsupervised learning

Use learning techniques for enabling machines to develop intelligence that can allow them to make intelligent human-like decisions.

NLP

Natural Language processing techniques to enable machines to peruse, interpret languages like English and articulate responses or frame sentences.

Python / R

Programming using new age languages like Python and R supported by Pandas libraries to develop AI, ML and Data Science models.

Image / Object recognition

Using techniques like Region-Based Convolutional Neural Networks (R-CNN) for image and object recognition.