Engineering cognitive solutions for multiple industries, with smart components, intelligent frameworks and predictive analytical intelligence
The decision support mechanisms in enterprises require self-learning, purpose-driven software applications. The success of any business will be determined by the technology applications that harness learnings from past data of an enterprise and use contextual data patterns needed for future decision making. We enable the transition towards next-generation of the digital workforce. We develop and maintain cognitive software applications by utilizing AI, interactive, predictive and contextual technologies.
We use NLP techniques for a wide range of solution practices in the cognitive space for effective human-machine interaction.
We make speech recognition algorithms to use for smarter user interactions for engaging solutions.
We build autonomous systems based on AI, developing predictive algorithms for a functional cognitive enterprise.
Understanding business lifecycles, we design smart, interactive conversational bots for industry users.
Lot of our implementation from security authentication to gamified user engagements are based on face detection technology.
We use AI-driven maneuvers with smart devices to capture user emotion and enhance customer experience.
We use SA as a critical element to analyze customer data and analyze behavioral patterns as symptoms to find answers.
We build autonomous systems based on AI, developing predictive algorithms for a functional cognitive enterprise.
Most of our recommendation engines are built for cognitive experience for users, based on the active and passive user behavioral patterns.
We have proven expertise of developing adaptive smart search and contextual browsing-based discovery platforms.
We specialize in extracting valuable and extremely relevant information across numerous industries using NLP and knowledge graphs.
We use semantic intelligence to develop complex solution frameworks for enterprise-wide confluence of data-driven intelligence.
Are your customers turning cold towards your products and services? Are they choosing your competitors over you? Is it getting difficult for you to meet their growing demands? If your answer to all these questions is a yes, it might be time to overhaul your customer experience strategy. The consumers of this digital era look for seamless, customized user experience in whatever solution or product they use. To meet their changing needs, businesses need to upgrade their tactics with the latest technologies and business models.
The ultimate prize for cybercriminals is to obtain access to other people’s money - so it’s no wonder that account takeover attacks are on the rise. In this article, originally published by Fraud Intelligence, Greg Hancell, Manager of Global Fraud Consulting at OneSpan, explains how banks can apply continuous monitoring and machine learning to defend against account takeover attacks.
The finance industry is a prime use case for machine learning, thanks to the abundant data sets, access to capital and strong incentive for efficiency and predicting future outcomes. While rule-based workflows are well embedded within the industry, many businesses are now turning to machine learning to automate the algorithm building process, especially when it comes to fintech.
“Alexa, transfer €70 to Peter.” Payments are going to be this simple very soon. You will have a smart robot telling you where to invest in, and providing you with personalized recommendations to manage your finances. All thanks to emerging FinTechs that are applying futuristic technologies and solutions.