As many businesses look toward productivity and automation of roles and tasks, Natural Language Processing sits at the heart of the opportunity. There is a great amount of potential for enterprises to adopt NLP into their organization, and the Best Innovation in NLP Award champions the providers at the head of the curve.
With a shortlist including Yseop, Creative Virtual and HCL Technologies, this was a tough category, but at The AI Summit HCL came out on top with their DryICE tool.
HCL’s DryICE solution extracts the content and context from both structured and unstructured data, and is able to identifying sentiment and trend over time, among many other impressive features. 
AI Business spoke to Kalyan Kumar, Executive Vice President and CTO for ITO and Digital at HCL, to find out his thoughts on receiving the award, the story behind DryICE and the future that lies ahead.
HCLFirstly, congratulations on winning the Best Innovation in NLP Award! How does it feel to win this category?

We are delighted to be selected as the Best Innovation in NLP. This award gives testimony to the innovation and pragmatic implementation of NLP in the 21st Century Enterprise.

 

When and how did your idea for NLP first come about, and how long did it take to develop?

HCL has an overarching Autonomics & Orchestration framework called DryICE. DryICE has over 40+ MicroServices which are enabled with an AI Foundation and Orchestration integration, applicable across Next Gen IT, Digital and IOT Use Cases. We took the Human2Human and Human2Machine interaction patterns and have applied the core NLP capability across Cognitive Service Desk, Intelligent Tech Support, Robotic Process Automation domains.

 

What particular features of the DryICE NLP make it stand out in the marketplace?

The DryICE NLP has a collection of algorithms which we put into a framework containing HCL’s optimised Algorithms and Ecosystem partner solution, which then creates a holistic NLP Offering. This includes specific areas around text extraction, Grammar Understanding, Meaning Matching of Situations to Actions, External Knowledge Pattern and aspects partner Algorithms around Emotion & Tone Analysis, Voice Processing etc.

 

How easy is it for the solution to be implemented and used by businesses?

The solution is embedded into multiple Solution Products in the DryICE Framework and is consumable as a XaaS Model, without doing all the heavy lifting.

 

Do you have plans to develop the DryICE NLP further? Are there any new projects or NLP tools on the horizon at HCL?

Yes. We have six products in the DryICE Framework, which is embedding the core NLP Engine across products like Lucy, iTS, iAutomate, Kelvin etc.

 

Which other NLP tools have inspired you, and which other companies do you see as leaders in this field?

We work with an ecosystem of partners including Microsoft, IBM Watson, OpenML, Amazon Web Services etc.

 

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