Artificial Intelligence (AI)

Artificial Intelligence (AI) attempts to transfer human learning and thinking to the computer and thereby provide it with intelligence. Instead of being programmed for any purpose, an AI can discover responses on its own and fix issues.

Intelligent Automation

Intelligent automation has great potential to automate non routine tasks involving intuition, judgment, creativity, persuasion, or problem solving. The decreasing costs of data storage and processing power are driving rapid developments in the field of Artificial Intelligence, creating a new breed of cognitive technologies with human-like capabilities such as recognizing handwriting, identifying images, and natural language processing. When combined with robotic process automation and powerful analytics, these cognitive technologies can form intelligent automation solutions that either directly assist people in the performance of nonroutine tasks or automate those tasks entirely.

Robotic process automation (RPA)

Pioneering enterprises are leveraging intelligent automation in a number of ways:

  • Wealth management firms are using IA to review and analyze portfolio data, determine meaningful metrics, and generate natural-language reports for their customers on the performance of each of their funds.
  • Global banks are leveraging IA to improve their regulatory compliance processes by monitoring all electronic communications of employees for indicators of non compliant activities.
  • Insurers are using IA to answer the queries of potential customers in real time and increase sales conversion rates.

The uses of intelligent automation are potentially limitless. They are also typically more expensive and take longer to implement than robotic process automation tools. Unlike RPA tools, which can be broadly applied, IA solutions require more extensive configuration and machine learning that is specific to a much narrower business purpose and the complex scenarios it may encounter.


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Natural Language Processing (NLP)

Nat­ur­al Lan­guage Pro­cessing is a field that cov­ers com­puter un­der­stand­ing and ma­nip­u­la­tion of hu­man lan­guage,

  • Cognitive computing
  • Natural Language Processing Techniques in the Enterprise Data World
  • Formulating responses to questions
  • Social media monitoring
  • Text analytics

Machine Learning

There has been a renewed interest in machine learning in last few years. This revival seems to be driven by strong fundamentals – loads of data being emitted by sensors across the globe, with cheap storage and lowest ever computational costs!

Machine Learning
Deep Learning

Deep Learning

Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.


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