Cognitive Technical Support       

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Cognitive Technical Support - overview


Overview

The Cognitive Technical Support department is focused on reimagining the world of IT services entrenched by AI, deep learning and cognitive technologies.  Our goal is to infuse cognitive technologies powered by Watson into the domain of IT services that are delivered via a mix of private, public and hybrid cloud based technologies.  We develop AI solutions and services intended for customer helpdesk operations, troubleshoot and triaging as well as preventive maintenance.

What comprises IT Support?

IT support is needed across the spectrum of service management beginning with customer help-desk where the problem is first reported, to the technical support agents who troubleshoot and triage to keep the infrastructure/applications up and running, all the way to the autonomous self-monitoring IT systems that can detect problems and self-heal to prevent future problems.  Traditionally this industry has been extremely human intensive mainly due to the complexity of tasks involved in maintaining applications and IT devices (servers, storage, network etc.).  However, the complexity of IT systems, their sheer scale and the large combinations of operating systems, middleware and applications that comprise any given managed system therein make automated service management a very hard research problem.

How can Cognitive Technologies Help?

A cognitive IT support system is defined as one that: (a) can diagnose problems related to  the IT entities  when they occur or can predict them before they will occur, (b) discover root case analysis of the problem and can resolve them automatically and (c) can learn and improve its understanding and resolution over time. Our aim is to build such a support system that has the following components:

  1. Mines  terabytes of operational day that are generated by IT entities every day to build machine learning models that detect patterns of failures
  2. Mine human conversations to correlate the learnt patterns to the operational data , the diagnosis of the root cause and finally to resolution actions
  3. Codify and store all the knowledge, patterns and insights in the form of IT knowledge graphs
  4. Create cognitive assists that use natural language understanding/AI and the codified knowledge graphs to aid the tasks of all human touch points in the system.



Team Updates

  • Gargi delivered Distinguished Lecture on Cognitive Computing and Customer Support at Model Institute of Engineering and Technology (MIET), organized the Association of Computing Machinery (ACM)MIET
  • Accepted: “Learning Relevance as a Service for Improving Search Results in Technical Discussion Forums” by Shivali, Shubham and Gargi et al. at 23rd IEEE ICWS


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