Measurable outcomes, not slideware.
Automated Quality engagements are designed around a small set of business outcomes we commit to at kickoff.
Manual QA reviews 3% of calls. Compliance risk lives in the other 97%.
Traditional QA can't scale to the volume of a modern contact center. Automated Quality closes the gap with calibrated scoring across every interaction.
- Sampling biasManual reviewers pick the calls they can reach — not the ones that matter most.
- Inconsistent scoringDifferent reviewers, different scores. Coaching becomes an argument.
- Delayed feedbackCoaching that arrives a week later doesn't change agent behavior.
A QA operating model, not just a scoring engine.
Every voice and digital contact scored against a calibrated rubric.
Miranda, mini-Miranda, disclosures, right-party contact, TCPA and industry-specific checks.
Beyond keywords — model-based scoring of tone, empathy and resolution quality.
Prioritized coaching queues for team leaders, tied to skill gaps and improvement plans.
Human reviewers calibrate the model, keeping scores defensible to agents and unions.
Quality trends by queue, product, geography and cohort — with drill-down evidence.
The automated quality architecture.
From sampled manual review to scored coverage of every interaction, with calibration and appeal built in.
- 01
Quality & coaching workspace
Scorecards, coaching queues, calibration sessions and agent-visible feedback with dispute handling.
- 02
Scoring & evaluation
LLM scoring against your rubric, confidence thresholds, sampling for human calibration and drift detection per model version.
- 03
Transcription & redaction
Speech-to-text across languages and channels, with PII/PCI redaction before evaluation and storage.
- 04
Interaction capture
Recordings, transcripts, screen and metadata drawn from the CCaaS platform and recording estate.
- 05
CCaaS, WFM & systems of record
Quality outcomes flowing into WFM, performance management and reporting.
What is automated quality management?
Automated quality management (AQM) is AI scoring of every customer interaction against the quality scorecard, replacing the traditional 2–3% manual sample. Each score links to the moment in the transcript that produced it, human calibration keeps the AI aligned to the rubric, and coaching queues are generated automatically from the findings so supervisors spend their time coaching rather than listening to calls.
Also known as: AI quality management, 100% QA coverage, auto QA.
Moving from sampled QA to 100% coverage in five steps
- Step 1
Rewrite the scorecard
Convert subjective criteria into observable, evidence-linkable behaviours an AI and a human can both score.
- Step 2
Calibrate against humans
Score a labelled set with both AI and evaluators until agreement clears the threshold you would accept from a new QA analyst.
- Step 3
Turn on full coverage
Score every interaction in shadow first, publishing results to supervisors before they affect agent records.
- Step 4
Automate coaching
Route findings into coaching queues with the exact transcript moment attached, and track whether behaviour changed.
- Step 5
Report the evidence
Publish program-level quality evidence to clients or business owners, replacing sample-based scorecards.
Manual sampled QA vs automated quality management
| Dimension | Manual sampled QA | Automated quality management |
|---|---|---|
| Coverage | 2–5% of interactions | 100% of interactions |
| Bias | Sample and evaluator bias | Consistent rubric, calibrated periodically |
| Time to finding | Days to weeks | Minutes after the interaction |
| Evidence | Evaluator notes | Linked transcript moments per score |
| Supervisor time | Mostly listening | Mostly coaching |
A six-step model, from assessment to managed operations.
Every engagement follows the same rhythm — so business, IT and delivery stay aligned from opportunity to outcome.
Rubric review and current-state QA audit.
Model, calibration and coaching workflow.
One BU, calibrated to human reviewers.
Integration with CCaaS and WFM.
Rollout across queues and geographies.
Ongoing calibration and rubric evolution.
Use cases already in production with enterprise clients.
Automated evidence for financial services, healthcare and collections disclosures.
Per-client scorecards, drill-down evidence and client-facing quality reporting.
Weekly coaching insights per agent from week one — not month three.
Discovery-to-close scoring for revenue teams, tied to CRM outcomes.
Grounded on your data. Governed on day one.
Every platform we implement is only as good as the retrieval, connectors and controls behind it. These are the horizontal solutions we ship with every engagement.
Scoping a Automated Quality programme? Send us the brief.
Four fields. Tell us the outcome and timeline and a delivery lead for this area replies with indicative scope, team shape and commercial options.
solutionAutomated Quality — routed to this team
Where this fits in our practice
Questions buyers ask us first.
- Will agents accept AI scoring?
- Yes — when it is calibrated to human reviewers, defensible on any single call, and paired with coaching rather than discipline.
- Which CCaaS platforms do you support?
- All seven leading platforms plus legacy recording sources like Verint, NICE, Calabrio and native cloud recorders.
- How is this different from speech analytics?
- Speech analytics finds keywords. Automated Quality scores full interactions against a calibrated rubric and drives coaching action.
How we work
Every CX and contact center program runs through one of four engagement models — advisory, implementation, managed operations or embedded pods.
pronix.ai is the AI & CX systems integrator practice of Pronix Inc.
One accountable delivery model: US-based architecture and program leadership with global engineering pods running 24×7 build, cutover and hypercare.
- Founded
- 2010 · Pronix Inc
- Headquarters
- 666 Plainsboro Rd, Suite 1361, Plainsboro, NJ 08536
- Delivery centers
- United States · India (Hyderabad) · EMEA
- Engagement model
- Fixed-scope implementation, managed run, staff augmentation and T&M Agile Teams.
Certifications
- AWS Certified (Solutions Architect, Developer)
- Amazon Connect specialty
- Genesys Cloud CX certified
- NICE CXone certified
- Salesforce certified (Service Cloud, Agentforce)
- Microsoft Azure AI certified
Partner tiers
- AWS — Advanced Tier Services Partner
- Genesys — Implementation partner
- Kore.ai — Reseller and Strategic Implementation Partner
- NICE CXone — Implementation partner
- Five9 — Channel partner
- Microsoft — Gold partner
- Salesforce — Consulting partner
Security questionnaires, controls documentation and named client references are available under NDA. More about Pronix Inc →
Book a working session with our automated quality team.
30 minutes. Your architecture, your data, your KPIs. You leave with a concrete pilot outline and a business case worth defending.