Test your chatbot before launch
Test your chatbot before launch with Argus AI: a practical, on-prem approach built for Azerbaijani teams.
Validate Your Chatbot's Performance Before Public Launch
Ensure your AI assistant is reliable, secure, and culturally nuanced with Argus, a comprehensive self-hosted AI testing platform. As one of the three core engines of the Argus ecosystem, this tool operates alongside QA and pentest engines under a single console and sign-in, allowing you to select your preferred judge model directly within the settings. By simulating thousands of realistic Azerbaijani synthetic users—each defined by a unique role, goal, language style, and knowledge level—Argus identifies critical vulnerabilities and accuracy gaps before they ever reach your end customers. Unlike standard testing tools, Argus treats adversarial personas as first-class citizens. It rigorously tests your assistant against frustration, contradiction, manipulation, and complex AZ→RU code-switching, recognizing that polite users are the least likely to expose system failures. By utilizing a native Azerbaijani LLM judge to score accuracy, tone, and safety, and treating the assistant as a black box via flexible connectors, Argus provides a realistic assessment of the actual customer experience while maintaining strict data sovereignty through its self-hosted architecture.
The Strategic Advantages of Argus
Massive Scale Simulation: Generate thousands of synthetic Azerbaijani personas with diverse behaviors to ensure comprehensive coverage.
Adversarial Resilience: Proactively detect prompt-injection, manipulation, and linguistic contradictions that could compromise your AI.
Native Linguistic Evaluation: Leverage an Azerbaijani-native LLM judge for precise scoring of formality, tone, compliance, and safety.
Production-Mirror Testing: Use black-box connectors (REST, Dify, Kommunicate, or browser automation) to test exactly what the customer accesses.
Immutable Audit Trails: Each run snapshots its evaluator configuration, ensuring historical results remain consistent and are not re-scored by future model changes.
Safe System Validation: Bounded per-assistant concurrency ensures that rigorous testing never evolves into a denial-of-service attack on your infrastructure.
Core Testing Capabilities
Adversarial Personas
Simulate challenging users who employ frustration, contradiction, manipulation, and AZ-RU code-switching to test the limits of your assistant.
Black-Box Integration
Test exactly what the customer sees via connectors for REST, Dify, Kommunicate, or browser automation.
Native LLM Judge
An Azerbaijani-native model evaluates responses based on accuracy, formality, safety, and compliance.
Knowledge-Driven Expectations
Expected behaviors are derived from your uploaded policy and knowledge documents, remaining human-overridable.
Configuration Snapshots
Every run snapshots its evaluator configuration, ensuring historical results are not altered by later model changes.
The Testing Workflow
Frequently Asked Questions
Is the readiness score a definitive release gate?
The readiness score is intended as a signal rather than a strict release gate, as there is currently no published agreement measurement against human reviewers.
How does Argus handle complex linguistic behaviors?
Argus generates synthetic users with diverse roles and styles, specifically focusing on adversarial behaviors like AZ→RU code-switching and manipulation to find edge-case failures.
Can the testing process impact my chatbot's availability?
No. Argus implements bounded per-assistant concurrency to ensure that the testing process does not become an attack on the assistant's availability.
How are the 'expected behaviors' determined?
Expected behaviors are proposed based on your uploaded knowledge and policy documents. These remain human-overridable, meaning a derived expectation is a proposal, not a final verdict.
What happens if I change my judge model after a test is complete?
Because each run snapshots its evaluator configuration at launch, finished runs are never re-scored against a model chosen after the run was completed.
Ready to secure your AI assistant?
Start testing your chatbot with Argus to ensure a professional and safe user experience.
Request a demo