AWS has infused its Contact Center Intelligence (CCI) suite with generative AI (GenAI).
While many will be more familiar with its Amazon Connect CCaaS platform, AWS provides the CCI suite to add AI and machine learning (ML) to third-party contact center platforms.
Amongst others, these third-party solutions include Avaya, Cisco, Genesys, and Talkdesk.
In augmenting these platforms, AWS delivers agent-assist, call analytics, and self-service virtual agent capabilities to end-users.
Now, AWS has laced these solutions with GenAI. The following demo from Dr. Andrew Kane, Principal Solutions Architect at AWS, highlights how.
During the demo, Kane notes the additional benefits GenAI delivers as part of the CCI suite:
- Improved call handling accuracy with faster contact resolution
- Script compliance checks and agent scoring
- Task automation that drives cost reduction
- A greater understanding of complex, natural language queries
- Conversational, accurate responses from trusted sources
- Abstractive call summarization
- Lower agent churn
Below is guidance on how it drives these outcomes after an intro into how AWS has embedded GenAI into its CCI suite.
Here’s How the CCI Suite Works
Call analytics sits at the CCI suite’s core. Only by getting to grips with how this works is it possible to understand how AWS is augmenting contact centers with GenAI.
First, note that AWS splits call analytics into live- and post-call analytics. Both have similar architectures – as evident in the following graphic.
However, one significant difference is that – with live-call analytics – it is possible to apply agent-assist. This works by sending the live transcript over to Amazon Lex line-by-line.
From there, Lex interprets the query and Kendra finds relevant information. It then passes this back to Lex, which surfaces those insights on screen, helping agents solve customer queries faster.
AWS has offered such capabilities for months. But now, with GenAI, AWS is taking this further.
This Is Where GenAI Comes In
AWS’s mission in GenAI is to democratize the technology, so companies of all shapes and sizes can access LLMs and build better experiences. As Kane puts it:
We’re not trying to restrict you to one or the other.
As such, AWS provides three methods to augment the reference architecture above with their preferred GenAI model.
These three methods hinge on three different apps: Amazon SageMaker, AWS Lambda, and Amazon Bedrock (as highlighted below).
