AI scoring on your criteria
Every call scored the same way. Calibration drift between reviewers disappears.
Auto-QA
QA software that reviews every call — at ~20% of the cost
InOro scores 100% of your calls against your own scorecard, minutes after they end. Same criteria on every call, every agent, every day — instead of a 2% sample and reviewer roulette.
Auto-QA — is automated quality assurance: AI evaluates each conversation against your evaluation criteria instead of a human reviewing a random sample. InOro maps your existing scorecard 1:1 — no simplification — and applies it to 100% of calls, with scores, justifications and per-agent trends.
How it works
Your scorecard, automated in three steps
- 1
Bring your scorecard
We map your current evaluation sheet 1:1. You edit criteria yourself, drag & drop; a new criterion takes minutes, not a change request.
- 2
AI scores every call
Against your criteria, contextually: completeness of questions, offer presentation, correct closing — not keyword matching. Score + justification ~30–60 s after each call.
- 3
Coach with data
Per-agent gaps with recordings to prove them, a best-calls library for training, and trends that show whether coaching works.
On every call
Everything a QA team does — on every call
Score with justification
Every point earned or lost is explained and linked to the transcript moment, so agents see why, not just how much.
Script & procedure adherence
Required questions, disclosures, offer presentation, closing — measured, not spot-checked.
Violation alerts
Missing identity verification, missing consent clause, critical language — flagged the same day.
Compliance solution →Coaching & best-call library
Data-driven 1:1s, exemplary recordings for onboarding, per-agent improvement plans.
Agent trends & comparisons
Rankings, history, new vs experienced, progress after coaching.
Agent performance analytics → At a glance
The economics of automated QA
- 100% of calls scored — manual QA reviews ~1–2%
- Auto-QA runs at ~20% of the cost of manual review (≈80% reduction)
- Typical shift: ~10 reviewers → 1–2 analysts on ready scorecards
- Your scorecard mapped 1:1, edited drag & drop
- Score + justification ~30–60 s after each call ends
- EU hosting or on-premise; from €0.05/min
The shift
What changes when QA covers everything
| Manual QA | InOro auto-QA | |
|---|---|---|
| Coverage | ~1–2% sample | 100% of calls |
| Consistency | varies by reviewer, needs calibration | same criteria, every call |
| Cost | ~10 people listening | system + 1–2 analysts (~20% of cost) |
| Systemic errors | may never enter the sample | visible in day one |
| Feedback loop | days–weeks after the call | same day |
| Reviewer role | listening & note-taking | analysis & coaching |
Coach smarter, ask the AI
Which agents scored below 70 on closing this week?
4 agents below threshold on 'correct closing': Marek (62 avg, 31 calls), Julia (66, 28)… Most common gap: no summary of arrangements. 12 example recordings attached.
Illustrative example with demo data.
What full coverage delivers
~80%
QA cost reduction
vs. manual baseline
10M+
Minutes analyzed
1,700+
Agents at a single client
Anonymized case: with full coverage, one client found agents mentioned the current promo in only 60% of calls — where it was mentioned, 92% ended in an order. A 2% sample had missed it entirely. QA team cost dropped to ~20% of the manual baseline.
Frequently asked questions
What is auto-QA?
Automated quality assurance: AI scores every call against your evaluation criteria instead of a human reviewing a sample. Scores come with justifications linked to the transcript.
Can we keep our current scorecard?
Yes — it's mapped 1:1, without simplification. You edit criteria yourself via drag & drop and can add a new one in minutes.
Do we still need QA people?
Yes, differently: instead of ~10 people listening to samples, 1–2 analysts work on ready scorecards — calibrating criteria, coaching agents, auditing edge cases.
How does AI handle context — sarcasm, interruptions, dialects?
Scoring is contextual: the model reads the whole conversation, not keywords. Test it on your own calls in the 30-day pilot — that's what it's for.
How fast are results?
Score and violations ~30–60 seconds after each call ends. Coaching happens the same day, not at month-end.
Does it work with our telephony?
Yes — API, SFTP or native connectors (Genesys, Avaya, Cisco). Agents change nothing.
Run your scorecard on 100% of last week's calls
30-minute demo — bring your scorecard, we'll show it automated. 30-day free pilot.