Artificial Intelligence

The term “Artificial Intelligence” is applied when a machine mimics “Cognitive” functions associated with human minds, such as “Learning” and “Problem solving”

Application of “Artificial Intelligence” to Enterprises can generate huge ROI for the business. Since the overall goal of intelligence is to allow machines to function in an intelligent manner, almost similar to how humans do, any enterprise can apply this to a large number of activities.

Across Retail, Travel, Hospitality, Banking and Telecom sectors, there are now a number of use cases where employee productivity is being improved with AI support, resulting in better outcomes for business. The simplest example here is that of ChatBOTs to guide Customers through the buying process or to help address grievances.

The other extreme is specialized software to recognize speech from a microphone, read license plates off a video file, identify faces on camera etc. all of which have wide-spread application across industries.

Sentiment Analysis of user sentiment from social media feeds like Twitter and Facebook, Natural language processing for self-service analytics, defect analysis using vision processing are some other areas where AI is being applied.
Internally, AI helps improve efficiency of daily tasks, guiding employees through incomplete/incorrectly performed tasks, suggesting improvements and even performing a part of the task.

If any of the above find resonance with your business needs and you wish to explore this next generation technology, you can benefit from our expertise.

Machine learning is a type of artificial intelligence (AI) lets computers learn without being explicitly programmed. It uses various statistical modelling techniques for converting big data into intelligence.

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Pursuing computing advances to create intelligent machines that complement human reasoning to augment and enrich our experience and competencies.

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AI applications include bot messaging/support, document discovery, voice analytics, text sentiment analytics and crawling techniques. Some common examples of machine learning applications include:

Forecasting sales based on historical numbers
Predict resale price of a used car
Guest sentiment analysis based on hotel reviews
Retail Consumer sentiment analysis based on twitter feeds
Recommendations from Amazon while browsing a company’s Facebook page
Product suggestions on an e-commerce website
Music suggestions on a music streaming app

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highlights

Natural language processing in apps
Intelligent recommendations and semantic search
Voice and text BOTs using LUIS
Forecasting using Azure machine learning
Intelligent algorithms to see, hear, speak, understand and interpret

Solutions

Retail Demand Forecasting, Social sentiment analysis, Purchase Assistance
Security Facial recognition, Video Clip/Voice Analysis
Hospitality Personal Assistant, Customer Experience, Geolocation based services
Banking Account Balance, Fraud Detection, Payment Reminders
Travel Search and compare, Live updates, Geolocation based services
Telecom Billing information, Payments

Benefits

Get insights from large volumes of data in a fraction of the time taken to do this manually
Improved Customer Satisfaction due to instant response and personalized Interaction
Reduced Customer operations costs as BOTS available 24*7 with no additional cost
Faster and improved Decision making support

Azure Bot Service	QnA Maker	Text Analytics API
Azure Machine Learning	HDInsight	R language

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The term “Artificial Intelligence” is applied when a machine mimics “Cognitive” functions associated with human minds, such as “Learning” and “Problem solving”

If any of the above find resonance with your business needs and you wish to explore this next generation technology, you can benefit from our expertise.

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