ASU™: Content meets context

With the power of Automatic Semantic Understanding (ASU), your virtual agent can make sense of even the most complex customer interactions.

Figuring out what your customers want shouldn’t be an uphill battle. With a bit of understanding - and a lot of advanced tech - conversational AI eliminates ‘false positive’ responses in 90% of cases.

Boost.ai’s Automatic Semantic Understanding (ASU™) helps your virtual agent know exactly what is important when in every customer interaction.

We understand how the machine learning models think and extract their semantic understanding.
 
 

From predicting to understanding

Smarter than the average algorithm, ASU™ helps your virtual agent get to the heart of a customers’ intent, giving them the information they’re actually looking for — with zero frustration.

 
 
Automatic Semantic Understanding is minimizing the risk of incorrect answers

Reduces ‘false positive’ responses

ASU™ is able to identify the relevant parts of a message and offer assistance while minimizing the risk of incorrect answers by up to 90%.

Introduction into semantic technology

Knows what it doesn’t know

Not all interactions should be automated. ASU™ lets your virtual agent intelligently identify what a human agent should handle and seamlessly reroutes customers to human support.

Through better understanding via ASU, conversational AI reduces traffic to your support channels, provides more helpful responses overall and makes every interaction with your brand worthwhile.

Understands multiple intents

Conversational AI can easily distinguish between multiple variables simultaneously, such as when customers ask for several products or services at the same time.

 
 

What’s a ‘false positive’?

A result that shows something is present when it really is not

Source: merriam-webster.com

Automatic Semantic Understanding: What it is and why it matters for your conversational AI chatbot
 
Boost AI’s Virtual Agent has the most advanced conversational AI
 

Make every interaction with your brand count

Customers don’t always communicate their needs clearly and even deceptively simple sentences can trip up lesser solutions. Learn how ASU™ can sift through noisy interactions to arrive at clear, clean and — most importantly — correct responses to every customer query.

 
 
ASU animation_ActionScript 3.0-compressed.gif
 
 

Not all algorithms are created equal

“Reaching a deeper understanding of conversational AI through deep learning”

Boost.ai Chief Data Scientist, Abhishek Thakur, explains the key differences that set virtual agents with ASU™ ahead of the competition in delivering the best customer experience across industries.

What the difference is between a chatbot with and without AI - read full article