AI Performance Checklist

Winning With Amazon Connect AI Isn't About More Automation.

Post launch tuning and monitoring guidance.

It's about faster decisions, better agents, and fewer wasted seconds. This checklist is built for leaders who already have AI live in Amazon Connect and want measurable improvements in handle time, first contact resolution, and agent effectiveness, without risking the customer experience.

10
Places AI improves metrics fast, without a full rebuild
6
Things we tell you not to automate yet
90 Days
Typical window to measurable, baseline-backed ROI
Checklist of AI tuning and monitoring tasks for an Amazon Connect contact center

Standard Consulting Partner since 2017

Quick Wins

Ten places AI improves metrics fast

Not a platform overhaul. These are the specific, narrow places Amazon Connect AI moves the needle fast, without touching the customer-facing experience.

  • Intent detection & intelligent routing
  • Real-time AI Agent Assist
  • Knowledge base search (RAG)
  • Auto-summaries and disposition notes
  • Automated QA scoring
  • Call reason classification
  • After-hours self-service automation
  • Multilingual understanding
  • Predictive intent nudging
  • Narrow-scope self-service containment

The Honest Part

What we won't automate, and where teams get this wrong

Most AI disappointment doesn't come from the technology. It comes from the wrong scope, and from skipping the groundwork that makes automation trustworthy.

What NOT to Automate (Yet)

  • Escalations and complaints
  • Billing disputes and refunds
  • Edge-case troubleshooting
  • Policy interpretation
  • High-emotion or high-stress calls
  • Conversations requiring explanation or judgment

Common Mistakes We Help You Avoid

  • Treating AI as a bot replacement instead of a performance tool
  • Skipping prompt and guardrail design
  • Over-automating before understanding call drivers
  • No baseline metrics or ROI hypothesis
  • Training AI on outdated or messy knowledge content
  • Relying on vendor demos instead of real call flows

Before You Tune Anything

The 7-Point Operational Checklist

This isn't the pre-launch Readiness Checklist. It's what we verify is still true once AI is already live and you're optimizing performance, not deciding whether to start.

  • Top Call Drivers Identified

    You know which call types actually drive volume, not a guess from six months ago.

  • Clean, Current Knowledge Base

    Content stays accurate and maintained, the single biggest lever on AI answer quality.

  • Defined Success Metrics

    AHT, FCR, and CSAT are tracked and trusted, so a tuning change has something real to move.

  • Structured Amazon Connect Flows

    Contact flows are documented and stable enough to layer AI on top without surprises.

  • Human Fallback Paths

    Every automated path has a clear, tested handoff to a person when it's needed.

  • Prompt Governance & Guardrails

    Scope, logging, and approvals exist, not just a model quietly making decisions.

  • Business and IT Alignment

    Both sides agree on what success looks like before anyone touches a dial.

Talk It Through First

Schedule an AI Performance Fit Check

We'll identify where Amazon Connect AI can deliver measurable ROI in under 90 days, based on your actual call drivers and metrics, not a generic feature list.


Proof, Not Hype

Tuning backed by a baseline, not a vendor demo

How this actually ships, not a theoretical optimization deck.

Real Talk

We'll tell you what NOT to automate, before you find out the hard way

Escalations, billing disputes, and high-emotion calls stay human in every build we scope. We'd rather lose a feature request than damage a customer relationship.

Real Pricing

Contact Lens sentiment and QA scoring, for about $1 a day

Automated QA scoring and sentiment analysis through Amazon Connect Contact Lens runs roughly $1 a day per eight-hour agent shift, real monitoring data without a big platform bill.

Certifications

AWS Certified Generative AI Developer – Professional badge
AWS Certified Machine Learning Engineer – Associate badge
AWS Certified AI Practitioner – Foundational badge

“DrVoIP has taken a very hands on approach to implementing our needs as we work to develop a replacement helpdesk solution. Our Helpdesk staff is very particular in their demands and DrVoIP has shown great flexibility in producing or adapting solutions to meet these. Additionally they provide regular status updates are always available to hop on a conference call to hash out any issues.”

Brian CoxIT Director, ASMR

“From watching his YouTube videos, we engaged Peter on numerous contact center projects, including migrating a portion of our Cisco UCCX contact center into AWS.”

Amir SafayanReal Estate Entrepreneur

“We wasted a month trying to DIY Connect. DrVoIP had us live in 4 days, with full IVR.”

CX ManagerSaaS Helpdesk

Where This Fits In What We Build

Performance tuning is the last mile, not the first step

This checklist assumes AI is already live. Here's where the earlier stages, and the bigger picture, live on this site.

AI Readiness Checklist

Not sure you're ready to launch AI at all? Start there before tuning anything.

Explore ›

AI Modernization Brief

The roadmap for adding these AI capabilities in the first place, before you get to tuning them.

Explore ›

Why AI Solutions

See the full picture of how DrVoIP applies AI across a contact center, not just this one checklist.

Explore ›


Common Questions

Frequently asked questions

No. The Readiness Checklist is a pre-launch self-assessment for whether you should start with AI at all. This Performance Checklist is for teams that already have AI live in Amazon Connect and want to tune it for better results.

Auto-summaries and disposition notes, automated QA scoring, and knowledge base search are usually the fastest, most measurable wins, because they don't touch the customer-facing conversation directly.

Because those calls need judgment, not scripted responses. Automating high-emotion or policy-dependent conversations is one of the fastest ways to damage trust and generate more complaints, not fewer.

Under 90 days is typical, once you have a baseline. Without one, you're guessing at improvement instead of measuring it, which is why baseline metrics come first on the operational checklist.

It starts as an AI Performance Fit Check, a focused review of what's live today. From there, some clients want a one-time tuning pass, others prefer ongoing monitoring. We scope it either way.


Further Reading

More on Amazon Connect AI, tuning, and monitoring

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AWS Bedrock, LangGraph, or CrewAI? Choosing an AI Stack That Survives Production

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Executive summary: Amazon Bedrock, LangGraph, and CrewAI are not three competing versions of the same product. Amazon Bedrock supplies managed access to AI models and supporting services. Frameworks such as Strands Agents, LangGraph, and CrewAI…
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Advanced Post Call Survey using Amazon Connect and LENS!

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Post Call Survey configurations Configuring a post call survey in Amazon Connect is very straight forward and many others have outlined strategies for doing such a configuration.    The usual strategy typically prompts the caller to enter…
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AI in Amazon Connect: How Bedrock, Lex, and SageMaker Work Together

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Artificial Intelligence (AI) is transforming customer service — but figuring out how it actually fits into Amazon Connect can feel like drinking from a firehose. If you’ve heard about Amazon Bedrock, Lex, and SageMaker, and wondered which…
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The DrVoIP AWS "Search Solutions" Guide

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which search service should I use One of the most common questions we hear from clients building on AWS especially those exploring generative AI is which search service should I use? AWS offers four distinct search and query services, each…

A practical comparison of AI orchestration frameworks for teams building past the proof of concept stage.

Replacing the old press-1-to-5 survey with sentiment analysis for a real read on call quality.

How three AWS AI services combine inside a contact center to handle understanding, response, and prediction.

A guide to the AWS services that make enterprise search and knowledge retrieval practical to deploy.

AWS Bedrock, LangGraph, or CrewAI? Choosing an AI Stack That Survives Production

Advanced Post Call Survey Using Amazon Connect and Lens

AI in Amazon Connect: How Bedrock, Lex, and SageMaker Work Together

The DrVoIP AWS Search Solutions Guide

AI Solutions

Conversation Intelligence

AI Solutions

Cloud Services


Ready to tune what's already live?

Tell us what's slow, inconsistent, or unmeasured today, and we'll tell you honestly which of these ten places would move the needle first.

FREE GUIDES & CHECKLISTS

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Amazon Connect AI Performance Checklist

One-page checklist of ten AI improvements, baseline metrics, human fallback, governance and activities that should remain human.

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