Being skeptical about any kind of hype, I was not excited about chatbots. I needed to understand the value before giving into yet another Silicon Valley hype. The opportunity came when I joined Cisco Hyper Innovation Living Labs (CHILL) in early 2017. Cisco being in the Enterprise Software space, works with many other enterprise customers. This means that they have a huge infrastructure, set of tools and processes for customer support that are ripe for automation.
While I can’t talk about the projects at my work here, it piqued my interest in chatbots, Natural Language Processing (NLP) and the overall conversational AI space. Although previously I have created rule-based home automation systems and language conversion software, this time it is my first foray into enterprise scale conversational AI with actual Natural Language Processing techniques.
I started looking into chatbot frameworks. Back in May 2017, Cisco acquired a conversational AI startup called MindMeld. I started using MindMeld NLP APIs and its conversational AI frameworks, having a deeper look into the concepts such as entities, intent etc. I kept digging more and found Rasa.ai – another enterprise scale conversational AI framework. And this time its open source! Few of my friends also mentioned ChatterBot – an open source conversational dialog engine. As I kept exploring, I came across many other conversational AI products both in consumer and enterprise space. I also came across a couple of bot analytics products – thanks to my EIR gig at Backstage Capital.
In this series of post – I am going to do a deep dive into chatbot frameworks, conversational AI products, bot analytics products and more that I find interesting along the way.