Argus for Telecom
Runs thousands of realistic synthetic users against your chatbot, scores every conversation and gives each release a readiness score.
Argus for Telecom: Know Your Chatbot Is Ready Before Subscribers Do
Telecom operators in Azerbaijan manage millions of subscriber interactions every day, spanning billing disputes, roaming queries, plan changes, and service complaints — all conducted across Azerbaijani and Russian, often within the same conversation, and always under strict service-quality SLAs. A single poorly handled exchange can erode subscriber trust and accelerate churn, yet traditional manual QA cannot scale to cover the full range of real-world conversation patterns before each release. Argus solves this by generating thousands of realistic synthetic Azerbaijani subscriber sessions and running them against your chatbot automatically, so every build is stress-tested against the actual linguistic and behavioral complexity of your contact center before a single live subscriber is affected.
Why Telecom Teams Choose Argus
Catch chatbot failures before they reach real subscribers, protecting your SLA commitments and preventing the subscriber churn that follows a poor automated interaction.
Test across Azerbaijani and Russian within the same session, accurately reflecting the code-switching reality of your contact center rather than treating each language as an isolated case.
Expose edge cases that polite test scripts miss — frustrated subscribers, contradictory requests, and prompt-injection attempts — so safety and reliability gaps are found in testing, not in production.
Eliminate the manual QA bottleneck by automating thousands of conversation checks that would otherwise require human reviewers, freeing your team to focus on higher-value work.
Prevent regressions with dedicated suites that re-run every previously identified failure on each new build, ensuring resolved issues stay resolved across the full release lifecycle.
Align product, QA, and operations around a single release readiness score per build, replacing subjective go-or-no-go debates with one consistent, objective signal.
What Argus Does for Telecom
Azerbaijani-Native Synthetic Subscribers
Argus generates thousands of realistic synthetic users modeled on Azerbaijani subscriber behavior — covering billing disputes, roaming queries, plan changes, and service complaints — so your chatbot is tested against conversations that actually reflect your customer base.
AZ↔RU Code-Switching Scenarios
Subscribers frequently switch between Azerbaijani and Russian mid-conversation. Argus deliberately tests these code-switching patterns, ensuring your chatbot handles language transitions gracefully rather than breaking or defaulting to the wrong language.
Adversarial and Edge-Case Testing
Beyond polite interactions, Argus simulates frustrated subscribers, contradictory requests, and prompt-injection attempts — the edge cases most likely to expose gaps in your chatbot's safety and reliability under real contact-center pressure.
Azerbaijani-Native LLM Judge
Every conversation is scored by an LLM judge built for Azerbaijani, evaluating accuracy, tone, formality, and compliance — not just whether the bot gave an answer, but whether it gave the right answer in the right way for your subscribers.
Release Readiness Score
Each test run produces a single readiness score for the release, giving your team an objective, consistent signal to decide whether a build is ready to go live or needs further work.
Regression Suites and Flexible Integration
Argus maintains regression suites that re-run known past issues on every build, and connects to your chatbot via REST API, Dify, Kommunicate, or browser automation — fitting into your pipeline without requiring a platform change.
How Argus Works in Your Release Cycle
Frequently Asked Questions
Does Argus require us to replace our current chatbot platform?
No. Argus connects to your existing chatbot via REST API, Dify, Kommunicate, or browser automation. It operates as a dedicated testing layer that sits alongside your current setup, leaving your platform and workflows unchanged.
How does Argus handle Azerbaijani and Russian in the same conversation?
Argus specifically generates code-switching test cases in which the synthetic subscriber moves between Azerbaijani and Russian within a single session, mirroring the real behavior of your subscriber base and exposing precisely how your chatbot responds to those mid-conversation language transitions.
What kinds of adversarial scenarios does Argus test?
Argus tests frustration escalation, contradictory or ambiguous requests, and prompt-injection attempts — scenarios that stress-test your chatbot's safety guardrails and behavioral consistency under the kinds of pressure common in high-volume contact centers. These edge cases are often the ones that slip through conventional QA scripts.
What does the readiness score actually measure?
The readiness score aggregates the results of all synthetic conversations in a test run — factoring in accuracy, tone, formality, compliance, and regression outcomes — into a single number that reflects how prepared the release is for live subscriber traffic. It gives every stakeholder a consistent, comparable benchmark across releases.
How do regression suites help with ongoing releases?
Each time a bug or failure is identified and fixed, it is added to the regression suite. On every subsequent build, Argus re-runs those cases automatically to confirm the fix held, preventing previously resolved issues from quietly reappearing in production and compounding over time.
Ready to Ship Chatbot Releases You Can Stand Behind?
See how Argus can fit into your release process — connect your chatbot and run your first synthetic test suite with the Allmaz team.
Request a demo