Too much to listen to
Manual listening limits coverage. Problems outside the sample may remain unseen.
Quality Assurance of Outbound Calls
Your AI Operation Partner. For outbound call quality.
Your AI Operation Partner for service quality. TeleAI automatically reviews all ingested, usable human-agent outbound calls and scores them against your custom rules. We work with your team to calibrate standards, review findings and turn them into lasting operational improvements.
THE LIMITS OF MANUAL REVIEWA small sample cannot tell the whole story.
When review capacity cannot keep up with call volume, managers see only part of the customer experience. More listening alone does not solve inconsistent judgments or repeated service failures.
Different reviewers, different scores
Unclear criteria leave room for conflicting scores and time-consuming disputes.
Problems surface too late
Backlogs delay feedback. A recurring issue may already affect more customers before coaching starts.
Scores without improvement
A deduction does not explain how to coach an agent or whether the issue has stopped recurring.
AI ANALYSIS + OPERATIONAL EXPERTISE
Broader coverage. Your standards. A team behind the findings.
TeleAI combines automatic scoring with the work that makes quality assurance useful: defining clear standards, validating judgments and helping supervisors act on the findings.
Full-coverage automatic QA
Review all ingested, usable human-agent calls within the agreed scope, rather than relying only on a manual sample. Make missing or unusable recordings visible in coverage reviews.
A wider, clearly defined review population.
Automatic scoring by your rules
Turn your service requirements into agreed checks and scoring rules. TeleAI helps clarify what counts as meeting a criterion and tests the interpretation with representative calls.
Scores assessed against your approved criteria.
A partner in quality improvement
Work with TeleAI on disputed findings, recurring weaknesses and practical coaching recommendations. Review later calls together to see whether the change holds.
Findings connected to owners and follow-through.
SEE WHAT A FINDING EXPLAINS
Not just a score. A reason to act.
When an agent discusses a loan amount, the approved disclaimer should make the distinction between the product limit and the customer’s final approved amount clear. This example shows how TeleAI helps your team identify omissions, review the evidence and improve agent practice.
Illustrative QA record · Not a customer result
After the introduction · Loan amount enquiry
Human outbound credit-marketing call: after the introduction, the customer expresses interest and asks about the maximum loan amount. The opening is omitted from this excerpt.
- Customer
I’m interested. What’s the maximum I can borrow?
- Human agent
You can apply for up to 50,000.
- Customer
How do I apply?
Custom check
Was the approval disclaimer stated when discussing the loan amount?
Automatic criterion score · Illustrative
0 / 10- Client-approved rule in this example
- When explaining the maximum amount in this example, the agent must add: “The actual loan amount is subject to system approval.” Your team approves the wording and applicable scope.
- Why it was flagged
- The agent says, “You can apply for up to 50,000,” but does not explain that the actual amount is subject to system approval. This illustrative finding assumes review of the full recording confirms the omission; the stated product maximum is not a personal approved limit.
The amount, rule and single-criterion score are illustrative, not an actual product offer, universal legal requirement, total call score or accuracy claim. Verify the complete recording and transcription quality before confirming an omission or taking action.
HOW WE MAKE THE JUDGMENT USEFUL
Confidence comes from calibration, not a promise of perfection.
Automatic scoring is the starting point. As your AI Operation Partner, TeleAI works with your reviewers on the standard, the exceptions and the evidence that should guide action.
Calibrate before expanding
Use representative calls and agreed human judgments to test each criterion. Resolve ambiguous wording and agree acceptable validation results before expanding the program.
Check evidence and exceptions
Review the call context behind a finding. Unclear audio, missing information and a disputed interpretation require further review, not an unquestioned conclusion.
Review misses as well as flags
Compare flagged and unflagged calls with human review. Use disagreements to refine rule definitions and test the revised interpretation on comparable calls.
Verify that coaching changes calls
Keep the review population and criteria comparable. Track whether the same issue recurs after coaching, and adjust the intervention with your supervisors.
AI OPERATION PARTNER
A quality program we build and improve with you.
Our value is the combination: AI analysis at scale, professional operating judgment and continued collaboration. Your supervisors get a partner who helps connect standards, findings and practical changes.
Build the standard together
We help translate your service goals into review criteria, plan the recording input and run a calibrated pilot with your reviewers.
Make findings actionable
We help distinguish an individual coaching need from a recurring policy or process gap, agree owners and prepare practical recommendations.
Keep improving the program
We review scoring disagreements and recurring issues with your team, validate changes and refine the next cycle of quality work.
AGREE WHAT BETTER LOOKS LIKE
Measure the quality of QA—and what changes after it.
Agree the baseline, population and review period before the pilot. Use comparable evidence rather than assuming more scores automatically mean better service.
- Coverage & turnaround
- Calls reviewed against eligible recordings; time from usable input to available findings.
- Review agreement
- Agreement with calibrated human review, alongside false flags and missed issues.
- Action completed
- Findings with an owner, completed coaching or process changes, and a follow-up review.
- Recurring issues
- Repeat findings in comparable later calls, with the context needed to interpret a change.
Before your quality pilot
Is this for human agents or AI calls?
This solution focuses on AI quality assurance of outbound calls made by human agents to customers. The AI reviews the conversation; it is not the service agent shown in the example.
Can every call be scored automatically with our rules?
Yes. TeleAI supports full automatic QA and automatic scoring of all ingested, usable calls within the agreed scope using your custom rules. Before launch, we confirm the input population, criteria and handling of missing or unusable recordings with your team.
How do we start with existing recordings?
We first review available recordings, formats, languages and the service context, then agree the input method and a representative pilot. Integration options and processing times are confirmed for your environment; we do not assume compatibility with every recording platform.
What if a supervisor disagrees with a score?
Review the original call and the approved criterion together. TeleAI helps examine ambiguity, document the agreed interpretation and validate any rule change. AI findings support human judgment rather than replacing it.
Does TeleAI stay involved after setup?
Yes. As your AI Operation Partner, we collaborate on the agreed review cadence, recurring issues, coaching recommendations and validation of improvements. The responsibilities and review scope are agreed with your team.
How are recording access and sensitive information handled?
Before data is shared, agree permitted use, authorized reviewers, access scope, retention and any required masking with your team. Deployment and processing arrangements are confirmed for the project and should follow your applicable requirements.
Bring your calls. Let’s build a better quality program.
Share your service goals, current review criteria and representative recordings. We will plan the scope, calibration and improvement work with your team.
