Machine Learning

As a machine learning company, we know that a challenging business environment drives industries to undertake constant digital initiatives for sustainable growth in the market. With the increase in data velocity, the task of making the best out of captured data is a challenge as well as an opportunity. Machine learning helps with automating the process of learning and knowledge discovery.

  • Self service ML and AutoML.
  • En-cash consumer preference and timeline events with Recommendations engine.
  • Customer segmentation and clustering.
  • Automate prediction and decision-making.

As a machine learning development company we ensuring reduced costs, increased time saving, automated operations, and enhanced productivity, we also help companies accelerate the end-to-end machine learning lifecycle in their organization.


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Extract useful information from images and surroundings for face recognition, biometrics, transportation, AR, and other use cases with computer vision algorithms.

The company situated in the US, primarily into Bike and ATV resale retail + wholesale business recently diversified into car retail resale business via acquisition and also launch of a new online platform for buying and selling cars.

Major CPG goods manufacturer in the UK wants to know the effectiveness of a certain kind of trade promotion ( on the shelf, a display coupled with discounts, volume promotions, etc.) and then use this information to maximize its business metric ( Market Share, GMV, Revenue, etc.) within multiple constraints of budget, price, target revenue, etc.

One of the biggest electronics retailers in Dubai operates 30+ stores and offers 15000+ different SKUs at competitive prices. The client prepares for the annual shopping festival/season which is the major period of demand and also depends upon ~20 categories (~500 SKUs) for most of its revenues.

Company in India which has exclusive rights to market and sell premium European brand of stockings and sports wear. The company places 150+ turner shelves across 50+ stores across India.

Singapore-based MRO company wants to rationalize the inventory of Spare parts to minimize overstocking carrying cost, CAPEX cost and penalties due to understocking.

The client is among the largest distributors of aircraft parts in the US. Wants an intelligent pricing model for its quotations process. There is no background data available about competitors or probable customers.

Machine Learning for Industries

Machine Learning is a fast-growing trend in the healthcare industry thanks to the advent of wearable devices and sensors that can use data to assess patient health in real time. The technology can also help medical experts analyze data to identify trends that may lead to improved diagnoses.

Banks and other businesses in the financial industry use Machine Learning technology for two key purposes: to identify important insights in data, and to prevent fraud. The insights can identify investment opportunities, or help investors know when to trade. Data mining can also identify clients with high-risk profiles, or use cyber-surveillance to pinpoint warning signs of fraud.

Technologies powered by Machine Learning capture, analyze, and use data to personalize the shopping experience in real time. Algorithms discover similarities and differences in customer data to expedite and simplify segmentation for enhanced targeting. In fact, Machine Learning capabilities can present online shoppers with personalized product recommendations while adjusting pricing, coupons, and other incentives in real time.

The automotive industry is taking steps to differentiate itself by leveraging Machine Learning capabilities and big data analytics to improve operations, marketing, and customer experience before, during, and after purchase. Predictive analytics lets manufacturers monitor and share vital information regarding potential vehicle or part failures with dealerships, reducing customer maintenance costs.

Government agencies, such as public safety and utilities, have a particular need for Machine Learning since they have multiple sources of data that can be mined for insights. Analyzing sensor data, for example, identifies ways to increase efficiency and save money. Machine Learning can also help detect fraud and minimize identity theft.

The data analysis and modeling aspects of Machine Learning are important tools to delivery companies, public transportation, and other transportation organizations.  In fact, analyzing data to identify patterns and trends is key to the transportation industry, which relies on making routes more efficient and predicting potential problems to increase profitability.

Machine Learning has become an integral part of the operations of most oil and gas companies, allowing them to gather large volumes of information in real-time and translate data sets into actionable insights. They now need to view data as an extremely valuable resource, with huge upside for companies with innovative, robust Machine Learning strategies. Saving time, reducing costs, boosting efficiencies, and improving safety are all crucial outcomes that can be realized from using Machine Learning in oil and gas operations.