Automatic scoring across 100% of volume
The AI applies your scorecard to every interaction: compliance, structure, tone, script adherence. The exhaustive, objective layer, available moments after hang-up.
AI Quality Monitoring
Compliance checked at 100%. Agents trained twice as fast.
Monitor quality. Guarantee compliance. Vocalcom Auto QM can analyze 100% of conversations to ensure compliance, while AI-powered quality monitoring reveals customer satisfaction without relying on surveys.
We needed 100% conversation coverage for compliance and smarter quality monitoring to understand customer satisfaction without surveys. Vocalcom delivered both.
Read Case StudyAI Quality Monitoring
Monitor quality. Guarantee compliance.
On an operation handling thousands of conversations a day, listening to everything is humanly impossible. Manual QM has therefore always worked on a handful of calls — hoping they were representative.
Manual quality monitoring
~2 %
- Hours of double-listening per supervisor
- A hand-picked sample, never representative
- A score that shifts with the evaluator and the day
- Breaches found weeks after the fact
- Coaching based on gut feel
AI Auto QM
100 %
- Every voice and digital conversation scored automatically
- The same criteria for everyone, without bias
- Compliance gaps caught while you can still act
- Coaching grounded in evidence, not impressions
- Supervisors coaching instead of listening
Your scorecard, not ours
The AI scores against your own criteria
You already have a quality scorecard — your mandatory disclosures, your script, your commercial criteria, your rating scale. You load it into the platform, and the AI evaluates every conversation against it.
Multiple scorecards can coexist: one per campaign, per role or per seniority. The same agent can be assessed differently depending on the activity they handle. Nothing to relearn: you keep your framework and only change the scale it runs at.
Automatic and manual
AI scores everything. Your supervisors decide what counts.
Automating everything is neither desirable nor socially acceptable. Auto QM combines both layers.
Manual criteria where it commits you
Bonuses, disputes, annual reviews: supervisors add their own criteria on sensitive cases. A decision that affects a person is still made by a person.
This hybrid approach also changes adoption: teams accept AI when it informs their judgment rather than replacing it.
How it works
Three steps, no system overhaul
- 1
Connect
Auto QM plugs into your voice and digital flows — natively if you run Vocalcom, by API if not. Your recordings, your CRM, your campaign references.
- 2
Analyze and score
Every conversation is transcribed, analyzed and scored against your scorecard moments after it ends. Compliance gaps trigger an immediate alert.
- 3
Coach and act
Dashboards surface coaching moments, recurring drivers and trends by team. Supervisors work on identified cases, not a random sample.
What the AI detects
Signals no human hears at this scale
Compliance and mandatory disclosures
Legal notices, consent capture, sector-required wording: checked on every conversation, with an alert when they're missing.
Dead air, crosstalk, tension
Abnormal silences, interruptions, emotional escalation: the markers of a conversation going wrong, detected across 100% of volume.
Dispute and churn risk
The phrasings that precede a complaint or a cancellation, surfaced before the case reaches legal.
What actually sells
The sequences your best agents use, identified and turned into training for the rest of the floor.
Automatic KPI tracking
AHT, first-contact resolution, escalation rate, contact drivers: measured continuously, with no manual logging.
Multichannel, one scorecard
Voice, WhatsApp, chat and email assessed on the same criteria, with a consolidated view per agent.
The Vocalcom difference
Every audited conversation trains your AI agents
Other quality monitoring tools analyze. Ours closes the loop: conversations scored by Auto QM feed directly into your Vocalcom AI agents. What your best agents do well becomes the automated agent's reference behavior; what Auto QM flags as a gap becomes a rule it won't repeat.
The result: your quality monitoring no longer just measures performance — it improves it, human and automated, in the same motion.
By role
What changes in practice
For quality and operations
- Every channel tracked from a single dashboard
- Your scorecard applied uniformly across the floor
- Coaching moments surfaced as they happen
- Filtering by agent, team, campaign or driver
- Evidence exports for audits and executive reviews
For sales teams
- The pitches that convert, identified and shared
- Recurring objections built into the playbook
- Comparison across teams, sites or outsourcers
- Compliance gaps caught before the complaint
- Shorter onboarding for new agents
Data and compliance
Your conversations stay yours
Hosting where you choose
You decide where your data is hosted, in line with your obligations and your clients' — decisive in regulated sectors and for BPOs bidding on public tenders.
GDPR compliance
Processing, retention periods and data subject rights handled at platform level, with the traceability an audit requires.
Certified security
ISO 27001, PCI-DSS and SOC 2 Type II: the certifications our banking, insurance and telecom customers already operate on.
Frequently asked
What quality teams ask us
Do we need to change contact center platform to use Auto QM?+–
No. Auto QM is native if you already run Vocalcom, and connects by API if your voice and digital flows live elsewhere. That matters for BPOs operating on several platforms depending on the client.
How soon after the call is the analysis available?+–
Moments after hang-up. The point of automated QM is to act while the situation can still be fixed, not to discover it three weeks later.
Can we keep our current scorecard?+–
Yes, that's the principle. You load your existing criteria and the AI scores against them. Several scorecards can run in parallel by campaign or role.
Does it cover written channels too?+–
Yes. Voice, WhatsApp, chat and email are assessed on the same criteria, giving a comparable score per agent whatever the channel.
What size of operation does this suit?+–
The value appears once listening to everything becomes impossible — in practice, from a few dozen agents. Past a hundred, the gap with manual sampling is dramatic.
Should agents be told?+–
Yes, and it's in your interest. The deployments that work are those where agents see their own evaluations and understand the criteria. A tool that develops people is accepted far better than one that watches them.
Audit your own operation in the demo
Bring real anonymized recordings and your current scorecard. We'll show you what Auto QM finds in minutes.