Blog: Capgemini CTO Blog
This blog explores the emergence of chatbots as a specific example of the impact of artificial intelligence technology on businesses in the modern day. It delves into their capabilities, both current and forthcoming, and expands on particular use cases and the potential for disruption of traditional company roles, both internal and external.
The Modern Age of Chatbots
Because of current advancements in natural language processing (NLP) and sentiment analysis techniques, fluid bi-directional communication in the familiar forms of text or speech between humans and intelligent systems has, in the recent years, become a reality. While the emergence of domain specific chatbots is not a particularly recent development, the methodology by which bots consume and interpret human input has changed dramatically, and consequently the level of depth of bot comprehension has grown tremendously.
A New Way of Communicating – Intelligent Automation in the Workplace
The new age of chatbots has ushered in a plethora of new applications in the workplace. Whereas before automated systems were confined to domain specific use cases, they are now sufficiently advanced to a more generalized purpose. Bots can allow employees to receive alerts, request information, perform actions, and complete tasks. Nascent technologies of conversational reporting using integration between bots and traditional data visualization platforms like Tableau and Power BI are emerging.
Capgemini’s Approach to Chatbots – A partnership with Kore.ai
The Kore.ai platform is an end-to-end environment for developing and deploying chatbots at the enterprise level. Kore offers a variety of out-of-the-box bots for rapid deployment and instant value add, as well as custom configuration options for businesses looking to design their own bots for specific use cases. Bots can be deployed on a wide variety of channels, ranging from messaging services like Slack and Facebook Messenger, to SMS and e-mail, to mobile apps and websites. The GUI based development environment, coupled with the seamless integration across channels, reflects a relatively tame learning curve for those who wish to develop custom bots.
Exploring the Potential of the Platform – Case Study
Capgemini partnered with Kore to demonstrate the potential business applications of Chatbots in a proof of concept project for a large multinational retail client. The bot demonstrations were divided into two separate categories:
- Employee assist bot focused on HR, e-commerce, and financial use cases, and
- Cognitive task bot focused on more general machine learning use cases.
The Power of the Cloud – Microsoft Azure Machine Learning Studio and Kore
While the potential of bots hosted locally or internally to deliver value to businesses became evident early on in the project, the true capabilities of the Kore platform were uncovered via its capability for integrating with cloud hosted platforms like Microsoft’s Azure Machine Learning Studio.
By leveraging the two platforms, one can develop bots on Kore to make API calls to the Azure, and thus employ the plethora of resources provided by the cloud based machine learning suite, such as distributed computing power and scalable data analysis and manipulation.
To demonstrate this capability to the client, we designed and deployed a rudimentary recommendation algorithm on Azure studio, which returned product recommendations upon calls being made from the Kore messaging app. The fictional product data was derived from an e-commerce website built for testing purposes, but the successful results imply enormous potential impact for prospective clients. The inherent scalability of the azure platform coupled with the flexibility of Kore deployment channels opens the door for offering intelligent automation and powerful machine learning solutions to all companies, regardless of size or resources.
Written By Connor Stefan and Anthony Brady
For more information regarding intelligent automation and the Kore platform, please contact Abhiroop Roy (Abirhoop.Roy@capgemini.com) or Alex Vayner (Alex.Vayner@capgemini.com)