Automation

Generative AI for Agent Augmentation: Agents Models not Language Models

ASAPP Chief Scientist Ryan McDonald on why effective agent augmentation requires Agent Models versus Language Models Read more

Ryan McDonald
Ryan McDonald, PhD

Chief Scientist at ASAPP

ASAPP - AutoSummary's 3R Framework Raises the Bar for Agent Call Notes

AutoSummary’s 3R Framework Raises the Bar for Agent Call Notes

The “3R Framework” of Reason, Resolution, and Result guarantees quality notes while saving minutes of agent time. Read more

Nirmal Mukhi
Nirmal Mukhi

Senior Director of ML Infrastructure

ASAPP - AutoSummary's 3R Framework Raises the Bar for Agent Call Notes
ASAPP - Not all automation is the same

Not all automation is the same

Where is automation the most impactful? Our AI models specialize in automating even the most difficult parts of customer interactions. Read more

Heather Reed
Heather Reed, PhD

Data Scientist, ASAPP

ASAPP - Not all automation is the same
What’s different about the ASAPP approach to agent efficiency?

Open the door to automation with JourneyInsight

Learn where you have inefficiencies and get insights powered by a 360 degree view of every workflow in your contact center. Watch now

Ted Burke
Ted Burke

Director, Product Management, ASAPP

What’s different about the ASAPP approach to agent efficiency?
ASAPP - Why its so challenging to map Agent Journeys™

Why its so challenging to map Agent Journeys

It isn’t easy to get a holistic view of how contact center agents spend their time to inform optimization. ASAPP Chief Scientist, Ryan McDonald explains why. Watch now

Ryan McDonald
Ryan McDonald, PhD

Chief Scientist at ASAPP

ASAPP - Why its so challenging to map Agent Journeys™

Is your technology working against your agents?

Stop building walls around your agents. Instead of damaging the relationship between you and your customers, help your agents collaborate with AI technology. Watch now

Judith Spitz
Judith Spitz, PhD

Advisor, ASAPP

ASAPP - Learning to recommend what agents should do

Learning to recommend what agents should do

Are your ML models learning the right things? Here’s what we discovered when we took a closer look at what agents do vs. what they should do in one situation. Read more

Chris Fox
Chris Fox

Staff Machine Learning Engineer

ASAPP - Learning to recommend what agents should do
ASAPP—The danger of only using containment rate to measure success

The danger of only using containment rate to measure success

Containment rate is not a good measure of success, used alone. A good metric will also consider if the customer’s need was met. Here’s how we measure. Read more

Bobby Kovalsky
Bobby Kovalsky

Customer Experience Strategist at ASAPP

ASAPP—The danger of only using containment rate to measure success
ASAPP—How do you know if ML-based features are really working?

How do you know if ML-based features are really working?

How do you measure efficiency and effectiveness in your contact center—for individual agents and for the team as a whole? Gain insight from our CX pros working with large consumer brands. Read more

Jonathan Rossi
Jonathan Rossi

Senior Customer Success Manager at ASAPP

ASAPP—How do you know if ML-based features are really working?
ASAPP—How do you find automation workflows for your contact center?

How do you find automation workflows for your contact center?

How do you identify the right workflows to automate in the contact center? And quickly implement them? ASAPP was awarded a patent for the technology to meet this challenge. Read more

Michael Griffiths
Michael Griffiths

Data Scientist, ASAPP

ASAPP—How do you find automation workflows for your contact center?