❝ Humans can typically create one or two good models a week; machine learning can create thousands of models a week. ❞
Most industries working with large amounts of data have recognized the value of machine learning technology. By gleaning insights from data often in real time, these organizations are able to work more efficiently and gain advantage over competitors.
To get the most value from machine learning, you have to know how to pair the best algorithms with the right tools and processes. We combine rich, sophisticated heritage in statistics and data mining with new architectural advances to ensure your models run as fast as possible – even in huge enterprise environments.
Combining – Vision, Data, Machine Learning and Languages to answer everyday questions
Become data "think-tanks"
Sales and account managers can get alerts from the algorithms about specific customers or deals that are at risk. Machine Learning gives management actionable, real-time insights about their customers and vendors.
Predictive analysis is playing an important role in HR departments today. Machine Learning models are being deployed to identify and recruit employees and also to make existing employees work more efficiently.
Marketing campaigns can be personalised with Machine Learning to meet the needs of prospective customers. Customers can be given special offers based on their previous buying patterns
The existing financial systems show historical financial transactions. But applications using Machine Learning show future opportunities and how to get more profits out of existing systems.
Let your insights drive the business
Smarter ways to power the world
Finding new energy sources, analyzing minerals in the ground, predicting refinery sensor failure, streamlining oil distribution to make it more efficient and cost-effective. The number of machine learning use cases we have implemented for enterprises is vast – and still expanding.
Analytics that create insight, impact and innovation for e-commerce
Websites recommending items you might like based on previous purchases are using machine learning to analyze your buying history – and promote other items you’d be interested in. We help to capture data, analyze it , find patterns and use it to personalize customer shopping experience and enhance future marketing campaigns.
Machine learning makes banking more personal
Banks and other businesses in the financial industry use machine learning technology for two key purposes: identify important insights in data and prevent fraud. We help business with insights that can identify investment opportunities or help investors know when to trade. Data mining can identify clients with high-risk profiles or use cyber-surveillance to pinpoint warning signs of fraud.
Analyzing real world evidence for personalized medicine
Explore ways to make intelligent data-driven decisions. Our focus lies in developing and applying machine learning and data mining tools to an array of different challenging problems from clinical genomic analysis, through designing clinical decision support systems, to analyzing real world evidence for personalized medicine.
Machine learning and intelligence for sensing, inferring, and forecasting traffic and events
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. We help enterprises leverage machine learning to build services and products that make use of both live streams of sensed information and large amounts of heterogeneous historical data.