Machine Intelligence + Innovative Commerce Solutions

Customer Success. Best ROI.

Our AI driven commerce services are designed to aid your team’s “Digital Intuition”, to enhance your customer experience, getting the best ROI, and focus on optimization. Our clients have benefited from our AI driven solutions for Recommendation Engine, Search Optimization, Personalization, Automated Machine Learning for CXOs and Labor Optimization in stores, to name a few.

Recommendation Engine

  • Recommendation algorithms aim to correctly predict user's preferences leading to increased purchases and better online experience for the user.
  • Different types of recommendation algorithms are presented to the user in the form of clickthrough carousel bands
  • Bestselling & trending
  • Frequently bought together
  • Popular, based on customer rating
  • View, based on product similarity
  • Promotions, based on user-product similarity

Search Optimization

Every search query is 'categorized' into one of available categories using ML algorithm and then the results are tailored using this.

Recommendation based on user Propensity & search query

2 users for the same search may be presented with different product options (Brand 1 & Brand 2). Propensity is measured for various end-points like product-category, sub-category, brand, age, etc.


Landing page personalization based on different features including buying behavior, previously evinced interests, device, location, demographic information, what similar users view or buy to present the products that may interest the user towards conversion. The personalization goes to the extent of defining dynamic user level promotions or personalizing the top-trending or most-popular products to interest the user towards making buying decisions.

Labor Forecasting Optimization

Provides forecasts for optimal allocation of labor at the store, selected department level by day and hour

Automated Machine Learning (AML)

AML automates building machine learning models on raw data thereby yielding a most accurate model.

AML enables the CXOs to assess whether any problem at hand can be solved using ML and if it’s worth investing into DSS to get more optimal models.


Automated Machine Learning (AML)

AML automates the stages of Machine Learning as:

  • Auto-processing raw data feed (normally 70% of work in DS)
  • Auto-detects variables and needs prediction parameter as input
  • Multiple algorithms work on the dataset in parallel
  • Model dashboard arranged based on best performing algorithm