Meet Dovetail: The first AI-powered, human-understanding engine

Resolve your customers’ issues with empathy

5 key ingredients of NLU

Dovetail™ uses Natural Language Understanding (NLU) to identify tone, sentiment, and even emojis in a chat.

Classification

Using just one classifier is so 2017. Deploying multiple classifiers in tandem can produce much higher precision. That’s why Dovetail tailors its use of select classifier combinations to specific industries and use cases. This way, you can have confidence at go-live that your conversational AI will deliver an outstanding customer experience.

Semantic Search

Effective NLU goes beyond intent classification, because parsing curveball questions can get tricky. With the power of semantic knowledge graphs, Dovetail seamlessly tackles a significantly higher percentage of user questions than your average AI chatbot.

The result? Fewer agent escalations, higher automation rates, and enhanced customer satisfaction.

Emotional Analysis

Are your customers feeling angry? Joyful? Fearful? Offer up different dialog, and actions flow based on the emotion of the user. Frustrated customers may just need the path of least resistance to a resolution. Meanwhile, happy customers may present an opportunity to upsell.

Using Positive and Negative sentiment—to understand how to progress and offer different things to the user—means that you can deliver an automated conversational experience without compromising a personalized and empathetic brand voice.

Emoji & Character Analysis

Some say it’s hieroglyphics reincarnated. Others say Gen Zers dream in it. Regardless, emojis have a place in the way we communicate with each other, with the brands in our lives, and now even with machines.

Dovetail deciphers tone, sentiment, and intent from emojis, so your customers can communicate in their most natural form.

Personalization Response Engine

No two customers are exactly alike nor should their experiences be—Dovetail can change the conversation based on the person. Understanding the user’s personas, where they’re coming from, whether a support page or sales page, and other context helps customize the conversation. This, together with our natural language generation engine, can help the customer experience feel more realistic and personal.