Stentor for Government
AI speech analytics that transcribes, scores quality, and detects complaints and risk across 100% of your calls — in your own private cloud.
Stentor for Government
Public agencies handle thousands of citizen calls every day, yet traditional quality assurance programmes review only a small, manually selected sample — leaving the vast majority of conversations unexamined. Complaints go unrecorded, compliance risks accumulate undetected, and service failures remain invisible until they become formal grievances or audit findings. Stentor is a speech analytics platform purpose-built for government bodies that cannot afford those blind spots. It transcribes, diarises, and scores every single call automatically, giving supervisors, quality teams, and oversight bodies a complete, searchable record of all citizen interactions rather than a partial snapshot.
Why Government Agencies Choose Stentor
Analyse 100% of citizen calls — not a sample — so no complaint, compliance risk, or service failure goes undetected in the unreviewed majority.
Maintain absolute data sovereignty with a single-tenant private cloud deployment inside your own infrastructure, where all processing and storage remain entirely under your agency's control with zero data egress.
Surface complaints and escalation signals automatically through real-time negative sentiment and compliance risk detection, enabling supervisors to respond before issues become formal grievances.
Produce transparent, audit-ready records for every call — timestamped transcripts, quality scores, risk flags, and human-override logs that give internal auditors and oversight bodies a clear, tamper-evident paper trail.
Handle the everyday linguistic reality of Azerbaijani public services with a purpose-built speech recognition engine that accurately processes mixed Azerbaijani and Russian conversations without degraded accuracy.
Reduce the manual review burden on quality teams by automating transcription, scoring, and risk flagging across all call volume, while preserving meaningful human oversight through the hybrid QA model.
Platform Capabilities Built for Public Sector Needs
Full-Coverage Transcription and Diarisation
Every call is automatically transcribed and speaker-separated, creating a complete, searchable record of all citizen interactions — eliminating the gaps that sampling leaves behind.
Complaint and Risk Detection
Stentor automatically flags calls containing complaints, negative sentiment, or compliance risk signals, allowing supervisors to prioritise follow-up and document issues before they escalate.
Purpose-Built Azerbaijani Speech Recognition
Trained specifically for Azerbaijani public-service speech, the engine accurately handles mixed Azerbaijani and Russian conversations — the everyday reality of citizen contact centres across the country.
Single-Tenant Private Cloud Deployment
Stentor runs entirely within your own infrastructure. No shared environment, no external API calls, no data egress — meeting the data sovereignty requirements that public bodies must satisfy by law.
Hybrid QA Scoring
Quality scores combine rule-based criteria, semantic AI analysis, and human override in a single workflow. This layered approach supports procurement and audit transparency by making every scoring decision traceable and explainable.
Structured Records for Audit and Oversight
All transcripts, scores, flags, and reviewer actions are stored with full timestamps and version history, giving internal auditors and oversight bodies a clear, tamper-evident paper trail.
How Stentor Works in a Government Environment
Frequently Asked Questions
Does Stentor send any citizen data to external servers or cloud providers?
No. Stentor is deployed as a single-tenant private cloud within your own infrastructure. There is no data egress of any kind — all transcription, scoring, storage, and access remain entirely under your agency's control. No shared processing environment is involved, and no external API calls are made during operation.
Can Stentor accurately handle calls where agents and citizens switch between Azerbaijani and Russian mid-conversation?
Yes. The speech recognition engine is purpose-built for Azerbaijani public-service contexts and is specifically designed to handle code-switching between Azerbaijani and Russian — a common pattern in government contact centres across Azerbaijan. This purpose-built approach delivers accurate transcription where general-purpose engines typically struggle.
How does the hybrid QA scoring model support audit and procurement transparency?
Each quality score is produced through a layered process: rule-based criteria are applied first, followed by semantic AI analysis of tone and content, and finally a human reviewer override where a supervisor judges it necessary. Every step is recorded with a timestamp and a clear rationale, giving auditors a fully traceable account of how each score was reached and who, if anyone, intervened.
Does Stentor review only a sample of calls, or every call?
Stentor analyses 100% of calls without exception. Every conversation is transcribed, speaker-diarised, scored, and checked for complaints and compliance risk signals — not a representative sample. This means no interaction falls outside the quality assurance process, regardless of call volume.
How does Stentor help quality teams manage large call volumes without simply adding headcount?
By automating transcription, scoring, and risk flagging across all calls, Stentor removes the need for staff to manually listen through entire call queues. Quality reviewers are directed only to calls that have been automatically flagged for complaints, negative sentiment, or compliance risk, allowing the same team to maintain meaningful oversight across a far greater volume of interactions than manual review alone would permit.
Ready to Bring Full Visibility to Your Citizen Contact Centre?
Talk to the Allmaz team about deploying Stentor within your agency's own infrastructure — and start turning every citizen call into an auditable, actionable record.
Request a demo