Aircall AutoQA, VoC, and QA Insights with Oversai
- Oversai connects to Aircall so support leaders can analyze voice interactions, call metadata, tags, notes, and outcomes without replacing Aircall.
- AutoQA scores Aircall conversations for accuracy, empathy, resolution quality, compliance, escalation judgment, and documentation quality.
- VoC and QA Insights turn calls into customer themes, coaching priorities, risk signals, and operational trends.
Aircall is often the voice layer for sales, support, success, and operations teams. Calls carry high-intent customer language, especially when customers are frustrated, confused, renewing, cancelling, requesting refunds, or escalating a sensitive issue.
That makes Aircall a valuable source for QA and Voice of Customer programs. Supervisors can see call volume, tags, notes, recordings, and routing data, but still struggle to understand the quality and customer signal inside every conversation.
Oversai connects to Aircall as an AI analysis layer for VoC, AutoQA, and QA Insights. Aircall remains the phone system. Oversai helps leaders understand the quality, sentiment, topics, and root causes inside the calls already happening there.
What The Aircall Integration Does
Oversai analyzes Aircall call content and selected metadata, then structures that data for quality measurement, customer feedback analysis, and CX observability.
Depending on the approved scope, that can include call recordings or transcripts, call direction, duration, user, team, number, tags, notes, comments, disposition, timestamps, missed calls, transferred calls, and selected CRM or help desk references.
| Aircall signal | Oversai output |
|---|---|
| Call recordings or transcripts | AutoQA scores, evidence, sentiment, topic classification |
| Tags, comments, and notes | QA context, disposition trends, workflow gaps |
| Team, user, number, and direction | Trends by queue, function, market, and call type |
| Transfers and missed calls | Escalation risk, routing friction, coaching opportunities |
Aircall's API reference documents calls, tags, comments, users, teams, numbers, and related resources: Aircall API references. Aircall also documents call comments and tags as structured call context that can support downstream workflows: Aircall API references.
Oversai uses this call context to help QA, CX, sales, support, and operations leaders measure quality at scale.
Prerequisites
Most teams begin with one call queue, team, number, market, or high-risk call type. Good first scopes include support escalations, billing calls, cancellations, complaints, renewals, onboarding calls, collections, account changes, and product support.
Prepare these inputs:
- The Aircall teams, numbers, tags, directions, queues, and call types to analyze first
- The call metadata, CRM links, and disposition fields that matter for reporting
- A QA scorecard for greeting, discovery, accuracy, empathy, resolution, compliance, and next steps
- A VoC taxonomy for topics, sentiment, root causes, customer effort, churn risk, and escalation reasons
- Data handling rules for recordings, payment details, identity information, and regulated conversations
Helpful internal pages include Aircall QA + VoC, Oversai AutoQA, and Voice of Customer analytics.
Setup Steps
A practical Aircall rollout usually follows seven steps.
- Choose the first Aircall scope. Pick the teams, numbers, tags, directions, call types, and linked workflows Oversai should analyze first.
- Authorize access. An Aircall admin approves the connection and the access needed for call records, metadata, and approved conversation content.
- Map metadata. Oversai maps user, team, number, direction, duration, tags, comments, transfer data, and linked customer identifiers into reporting dimensions.
- Configure AutoQA. QA leaders define criteria for opening, verification, discovery, accuracy, empathy, resolution, compliance, escalation, and documentation.
- Configure VoC. CX leaders define themes such as billing confusion, product gaps, cancellation language, complaint drivers, repeat contacts, and customer effort.
- Calibrate sample calls. Supervisors review scored examples to tune evidence, thresholds, compliance exceptions, and human-review routing.
- Route QA Insights. Send critical failures, coaching moments, churn risk, and process gaps to supervisors, operations, product, or revenue teams.
What VoC Looks Like Once Connected
Oversai can classify customer language from calls into topics, sentiment, objections, complaint signals, churn risk, product gaps, repeat-contact drivers, and unresolved issues. Leaders can review those themes by team, call type, number, customer segment, geography, product line, or linked workflow.
A support leader might see that callers are repeatedly confused about one policy. A product leader might see a defect described in customer language before ticket volume spikes. A revenue leader might see cancellation risk that never appears in a survey.
That is the value of VoC from Aircall: spoken customer feedback becomes structured enough for teams to act on.
What AutoQA Looks Like Once Connected
AutoQA evaluates Aircall conversations against your team's call quality standards.
Oversai can score whether the agent verified the customer appropriately, understood the issue, asked the right questions, used accurate information, showed empathy, handled objections, followed compliance steps, resolved the issue, and documented next steps.
Voice QA also benefits from context. A call may end politely but still need review if the customer repeated the same issue, the transfer path was avoidable, or the agent missed a compliance statement.
Oversai surfaces the evidence behind each score so reviewers can focus on calibration, coaching, and high-risk exceptions.
What QA Insights Look Like Once Connected
Supervisors can compare quality by team, queue, number, call direction, tag, issue type, region, customer segment, or transfer path. Leaders can see whether low scores line up with negative sentiment, repeat calls, missed calls, long hold times, or complaint-heavy topics.
Examples:
- Billing calls have strong tone but weak next-step clarity
- One number receives more cancellation language than other queues
- Transfers increase when a specific product issue appears
- Compliance language is inconsistent during refund or payment calls
- New agents need coaching on discovery questions before escalation
These patterns help teams improve the call workflow, not only individual agent performance.
Example Use Cases
Aircall teams often use Oversai to:
- Score more voice interactions than manual call sampling can cover
- Detect churn, complaint, refund, and escalation language from live support calls
- Audit compliance-sensitive calls with evidence and human-review routing
- Compare QA and VoC signals by queue, market, number, tag, or team
- Identify call reasons that should become product fixes, help center content, or workflow changes
- Build coaching queues from actual call evidence
For related guidance, read Customer support QA benchmark metrics and Customer support sentiment analysis software. For commercial planning, see Oversai pricing.
Bottom Line
Aircall gives teams the voice workflow. Oversai helps leaders understand the quality, customer signal, and operational risk inside that workflow.
Together, Aircall and Oversai help teams move from sampled call QA and delayed feedback to continuous AutoQA, VoC analysis, and QA Insights across voice support.
Frequently Asked Questions
Does Oversai replace Aircall?
No. Oversai works above Aircall as an AutoQA, VoC, and QA Insights layer. Teams can keep using Aircall for voice while leaders analyze quality and customer signal in Oversai.
What Aircall data can Oversai analyze?
Oversai can analyze approved call content, transcripts or recordings, users, teams, numbers, tags, comments, direction, duration, transfer context, timestamps, and linked customer metadata depending on scope.
Can Oversai evaluate phone compliance and escalation quality?
Yes. Oversai can help score required disclosures, verification steps, policy adherence, escalation judgment, documentation quality, and other call-specific QA criteria.