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self-healing, reliable
voice agents

Teams spent significant time and resources on manual testing processes that lacked efficiency and scalability

Every update to prompts or functions required repeated, manual retesting—introducing inconsistencies and errors

There was no clear insight into where voice agents struggled or failed during actual customer interactions

Analytics lacking in details to pinpoint gaps in AI system performance or understand agent behavior under pressure

Testing was limited to a few hand-crafted scenarios, and continuous monitoring was difficult to maintain at scale.

Run thousands of concurrent calls in minutes, enabling high-volume testing that replaces manual processes

Automatically flag and convert real customer interactions into future test cases, ensuring continuous iteration and improvement

Instantly retest prompts and functions, with detailed analytics and performance scoring for every test case

Identify where AI systems fall short with scenario-level analytics and clear metrics that highlight performance gaps

Save up to 5,200 hours and $520K per year by automating testing, generating dynamic scenarios, and seamlessly integrating live traces into golden datasets

Monitoring was passive and labor-intensive, offering minimal insight into live performance issues

Teams lacked real-time visibility into problems like hallucinations, latency, or underperforming responses

It was difficult to identify, prioritize, and respond to the most impactful issues in production environments

Calls and traces were used reactively for debugging, without a structured process for systematic improvement

Without a unified system for post-deployment analysis, response to issues was slow and performance optimization lagged

All production calls are actively monitored and scored using LLM judges, enabling consistent evaluation at scale

Live calls are automatically tracked for hallucinations, latency, and performance degradation, with issues flagged in real time

Get clear visibility into where your AI voice agents need attention, backed by detailed, scenario-specific analytics

Flagged calls and traces can be instantly turned into test cases and added to your golden dataset for continuous learning

Receive real-time alerts and access a robust analytics platform that surfaces system gaps, user patterns, and optimization opportunities

Teams struggled to generate comprehensive performance reports, limiting transparency and customer confidence

It was difficult to prove adherence to current or emerging AI regulations, putting teams at risk of falling out of compliance

System monitoring lacked accuracy and clarity, with no automated way to validate or explain AI behavior

Without clear accountability or reporting, enterprise clients lacked confidence in the reliability and responsibility of AI systems

Teams were not equipped to respond to audits or keep pace with fast-moving AI compliance standards and best practices

Detailed reports that highlight AI accuracy and reliability, to help you build trust and close enterprise deals with confidence

Stay ahead of AI Voice Agent regulations with continuous monitoring and reporting that aligns with both current and evolving standards

Clear, granular insights into AI decision-making, ensuring accountability and visibility into system behavior

Maintain fully documented performance logs, compliance metrics, and a complete audit trail—making audits seamless and stress-free

Receive real-time updates and stay continuously compliant as industry regulations and ethical expectations evolve