Use cases · Stentor

Score call-center agent performance

Score call-center agent performance with Stentor: a practical, on-prem approach built for Azerbaijani teams.

Automated QA: Score Every Call, Not Just a Sample

Traditional quality assurance teams have long relied on random sampling to evaluate agent performance, a method that inherently leaves the vast majority of conversations unreviewed and allows critical compliance gaps to go undetected. Stentor, developed by Allmaz, eliminates this blind spot by transcribing, diarising, and scoring 100% of your call-center conversations. By moving from a sampling model to total coverage, organizations can identify systemic issues and individual performance trends that were previously invisible. Engineered for the specific linguistic landscape of the region, Stentor utilizes purpose-built speech recognition designed to handle the complexities of the Azerbaijani language and the frequent mixed AZ/RU code-switching common in daily operations. To ensure maximum security, the entire system operates within a single-tenant private cloud, ensuring that your sensitive voice data remains protected with no data egress, combining high-scale AI efficiency with enterprise-grade privacy.

Capabilities

Strategic Advantages for QA Teams

Total Visibility: Analyze 100% of calls to ensure no performance dip or compliance risk is missed due to sampling errors.

Linguistic Precision: High-accuracy transcription for Azerbaijani and mixed AZ/RU speech, capturing the true context of every interaction.

Proactive Risk Management: Immediate detection of complaints and negative sentiment, allowing supervisors to prioritize high-risk calls.

Balanced Evaluation: A hybrid scoring model combining rule-based logic, semantic AI, and human override for objective yet flexible grading.

Absolute Data Sovereignty: Single-tenant private cloud deployment ensures all audio and transcripts stay within your own infrastructure.

Standardized Performance: Eliminate evaluator bias by applying consistent, objective scoring criteria across all agents and shifts.

Advanced Agent Performance Evaluation

100% Call Analysis

Stentor processes every recorded conversation rather than a random sample, giving QA managers a complete and unbiased picture of agent performance across all queues and time periods.

Transcription and Speaker Diarisation

Each call is automatically transcribed and separated by speaker, so reviewers can instantly see who said what — without listening to the full recording.

Purpose-Built Azerbaijani Speech Recognition

The speech-to-text engine is designed specifically for Azerbaijani and handles natural code-switching between Azerbaijani and Russian, reflecting how agents and customers actually communicate.

Complaint and Sentiment Detection

Stentor flags calls containing complaints, negative sentiment, or compliance risk signals, enabling supervisors to intervene quickly and address issues before they escalate.

Hybrid QA Scoring

Scores are generated through a combination of rule-based criteria, semantic AI understanding, and human override capability — so automated efficiency never comes at the cost of human judgement.

Single-Tenant Private Cloud

All processing happens within your own dedicated environment. No call audio, transcripts, or scores leave your infrastructure, supporting data privacy and regulatory requirements.

From Call Recording to Agent Score

1Call recordings are ingested into your single-tenant Stentor environment — no data leaves your infrastructure at any point.
2Stentor transcribes each conversation using its purpose-built Azerbaijani speech-to-text engine and separates agent and customer speech through diarisation.
3The hybrid scoring engine applies your rule-based QA criteria alongside semantic AI analysis to detect complaints, negative sentiment, compliance risk, and adherence to scripts or policies.
4QA supervisors review flagged calls, apply human overrides where needed, and access consolidated performance dashboards for individual agents and teams.
5Coaching priorities and compliance reports are generated based on complete call data, enabling targeted feedback rather than guesswork from sampled reviews.

Frequently Asked Questions

Does Stentor really analyse every call, or is there still sampling involved?

Stentor eliminates sampling entirely. It analyses 100% of your calls, meaning every single conversation is transcribed, diarised, and scored to provide complete operational visibility.

How does Stentor handle agents who switch between Azerbaijani and Russian mid-call?

The system uses a purpose-built speech-to-text engine specifically designed for the Azerbaijani market. It natively handles mixed AZ/RU speech, ensuring that language-switching does not result in transcription gaps or lost context.

Can our QA team adjust or override the automated scores?

Yes. Stentor employs a hybrid scoring model. While rule-based logic and semantic AI provide the initial score, human supervisors have full override capability to ensure final judgements remain accurate and nuanced.

Where is our call data processed and stored to ensure privacy?

All data is processed within a single-tenant private cloud environment dedicated to your organization. Because there is no data egress, your recordings and transcripts never leave your secure infrastructure.

What specific risk signals can the system detect automatically?

Stentor is configured to automatically flag complaints, negative sentiment, and compliance risk patterns. These parameters can be aligned with your specific internal QA framework and regulatory requirements.

Ready to Move Beyond Sampling?

See how Stentor can give your QA team full visibility into every agent conversation — without compromising data privacy. Contact Allmaz to arrange a demonstration tailored to your call-center environment.

Request a demo