Overview
Bluejay provides end-to-end testing for AI voice agents through real-world simulations, enabling teams to stress-test their agents with ease.
Key Features:
- Auto-generated scenarios
- A/B testing and red teaming
- Multilingual and accents support
- System observability
- Robust technical evaluations
Use Cases:
- Testing AI agents before deployment
- Identifying vulnerabilities in agent performance
- Improving user experience through real-time insights
- Automating daily updates for team collaboration
- Enhancing agent reliability and accountability
Benefits:
- Increased testing efficiency
- Reduced manual testing efforts
- Improved agent performance metrics
- Enhanced trust in AI interactions
- Faster deployment cycles
Capabilities
- Learns an agent's goals and behavior to build targeted test coverage for voice and text agents
- Generates large-scale synthetic “digital human” customers with language, accent, and emotion variation
- Auto-creates diverse real-world scenarios (orders, appointments, refunds, claims, security checks)
- Executes thousands of simulated interactions to compress a month of customers into minutes
- Runs A/B comparisons and adversarial (red-team) stress tests across agent versions
- Collects quantitative telemetry: latency, success rate, transfer-to-human rate, hallucination rate, duration
- Surfaces real-time dashboards, edge-case breakdowns, and exportable QA reports
- Provides a conversational “Ask Bluejay AI Anything” UI to query test results and incidents
- Sends automated performance alerts and daily updates to Slack, Microsoft Teams, or similar tools
- Offers production observability (Skywatch) to analyze live calls, failures, and regressions
- Outputs actionable QA artifacts: bug lists, ranked behavioral metrics, remediation guidance
- Supports continuous test→iterate cycles allowing teams to re-run suites and validate fixes
Add your comments