Detect complaints in calls
Detect complaints in calls with Stentor: a practical, on-prem approach built for Azerbaijani teams.
Automated Complaint Detection Across Every Call
Customer complaints buried in call recordings often cost teams valuable time, damage long-term relationships, and create significant compliance exposure. Traditional manual sampling only catches a fraction of these issues, leaving the majority of customer friction invisible. Stentor, developed by Allmaz, eliminates these blind spots by analysing 100% of your calls. By transcribing, diarising, and scoring every single conversation, the system surfaces complaints, negative sentiment, and compliance risks in real-time, allowing your team to intervene before issues escalate. Engineered specifically for the linguistic nuances of the region, Stentor features a purpose-built Azerbaijani speech-to-text engine that seamlessly handles mixed Azerbaijani and Russian conversations. To ensure maximum security and regulatory adherence, the platform operates within a single-tenant private cloud. This architecture guarantees that your sensitive voice data and transcripts never leave your controlled environment, providing a secure foundation for comprehensive quality assurance.
Why Teams Choose Stentor for Complaint Detection
Complete Call Visibility: Analyse 100% of conversations to eliminate the risks and blind spots associated with manual sampling.
Localized Linguistic Precision: Purpose-built for Azerbaijani speech, including the ability to process mixed Azerbaijani and Russian dialogue common in local contact centres.
Prioritized QA Workflows: Automatically flag complaints and negative sentiment, transforming random reviews into a prioritized queue of high-risk interactions.
Proactive Compliance Management: Identify regulatory and compliance risks at the individual conversation level to prevent unnoticed violations.
Enterprise-Grade Data Sovereignty: Deploy via a single-tenant private cloud with no data egress, ensuring your information remains within your infrastructure.
Human-in-the-Loop Control: Maintain final authority over quality decisions through human override capabilities for all AI-generated scores.
How Stentor Detects and Surfaces Complaints
100% Call Analysis
Every recorded call is processed — no sampling thresholds, no missed interactions. Complaints that would have slipped through a manual review cycle are captured consistently.
Transcription and Speaker Diarisation
Stentor transcribes each call and separates agent and customer speech, making it straightforward to pinpoint exactly who said what and when a complaint moment occurred.
Azerbaijani-First Speech Recognition
The speech-to-text engine is purpose-built for Azerbaijani and handles code-switching between Azerbaijani and Russian — a practical necessity for teams operating in Azerbaijan.
Complaint and Sentiment Detection
Negative sentiment signals and explicit complaint language are detected at the utterance level, giving supervisors a clear, timestamped view of where conversations turned difficult.
Hybrid QA Scoring
Scoring combines rule-based checks, semantic AI evaluation, and human override capability. Teams can enforce specific compliance rules while still benefiting from AI-driven nuance detection.
Private Cloud Deployment
Stentor runs in a single-tenant private cloud. Call audio, transcripts, and scores remain within your infrastructure — no third-party data sharing required.
From Call Recording to Complaint Alert in Four Steps
Frequently Asked Questions
Does Stentor really analyse every call, or is there a practical limit?
Stentor is designed to process 100% of recorded calls without sampling caps. The system is built to scale according to your specific call volume within your dedicated private cloud deployment.
How does Stentor handle conversations that switch between Azerbaijani and Russian?
The speech-to-text engine is purpose-built for the Azerbaijani market, meaning it can accurately transcribe mixed Azerbaijani and Russian speech within a single interaction, reflecting real-world language patterns.
What happens when the AI score does not match a reviewer's judgement?
Stentor utilizes a hybrid scoring model that supports human override. QA reviewers can manually adjust or replace any AI-generated score, ensuring that human expertise remains the final authority in the quality process.
Where is our call data stored, and who can access it?
All data is stored in a single-tenant private cloud. Your audio files, transcripts, and scores remain within your own environment and are never shared with or accessible by other tenants or external parties.
Can we define our own complaint or compliance rules in addition to the AI detection?
Yes. The hybrid QA scoring model includes a configurable rule-based layer. This allows your team to set specific compliance requirements or internal quality standards that work alongside the semantic AI detection.
Start Detecting Complaints Across Every Call
See how Stentor can give your QA team full visibility into customer complaints and compliance risk — without sampling, without data leaving your environment, and without replacing your reviewers. Get in touch with the Allmaz team to arrange a demonstration.
Request a demo