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Twilio: Harnessing The Power of AI (Artificial Intelligence)


On the earnings call, CEO Jeff Lawson noted: “We have the opportunity to change communications and customer engagement for decades to come.”

And yes, as should be no surprise, one of the drivers will be #AI (Artificial Intelligence).  Just look at the company’s Autopilot offering (at today’s Signal conference, Twilio announced that the product is generally available to customers).  This is a system that allows for the development, training, and deployment of intelligent bots, IVRs and Alexa apps.

Now it’s true that there is plenty of hype with #AI. Let’s face it, many companies are just using it as marketing spiel to gin up interest and excitement.

Yet Autopilot is the real deal. “The advantage that’s unique to Twilio’ s #API platform model is that we build these tools in response to seeing hot spots of demand and real need from our customers,” said Nico Acosta, who is the Director of Product & Engineering for Twilio’ s Autopilot & #Machine _Learning Platform. “We have over 160 thousand customers of every size across a huge breadth of industries and we talk to them about the solutions they need to improve communication with their customers. What do they keep building over and over? What do they actively not want to build because it’s too heavy a lift? Those conversations inform the products we create that ultimately help them differentiate themselves through better customer experience.”

AI Innovation

Consider that Autopilot breaks the conventional wisdom that there is an inherent trade-off between operational efficiency and customer experience.  To do this, Twilio has been focusing on pushing innovation with #AI, such as with:

·         Classification: This involves grouping utterances and mapping them to the correct task. With #AI, the system gets smarter and smarter.

·         Entity Extraction: This uses #NLP (Natural Language Processing) to locate details like time, place, cities, and phone numbers and so on. This means it is easier to automate repetitive tasks like setting up appointments (if the customer says “7 at night,” the NLP will understand this).

 

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