A system for synthesizing real IVR scenarios, automatically reproducing test scenarios, and providing accurate reports on those scenarios. An IVR tester uses a telephony device (website, mobile app, VOIP, etc.) and an automated IVR test case generator to place test calls to an IVR system. The automated IVR test case generator intercepts and collects the phone call's audio stream, dual-tone multi-frequency signals, and available metadata (e.g., response times, post-speech silence timeout, etc.). Once the call is complete, the automated IVR test case generator pre-populates a webpage or other user-interface technology and a database with the audio stream, dual-tone multi-frequency signals, and available metadata from the test scenario phone call. The IVR tester may then save that test scenario and continue to the next scenario. The saved scenario may now be used automatically by the IVR test case generator for regression testing or duplicated and edited for use in other systems.

A system for synthesizing real IVR scenarios, automatically reproducing test scenarios, and providing accurate reports on those scenarios. An IVR tester uses a telephony device (website, mobile app, VOIP, etc.) and an automated IVR test case generator to place test calls to an IVR system. The automated IVR test case generator intercepts and collects the phone call's audio stream, dual-tone multi-frequency signals, and available metadata (e.g., response times, post-speech silence timeout, etc.). Once the call is complete, the automated IVR test case generator pre-populates a webpage or other user-interface technology and a database with the audio stream, dual-tone multi-frequency signals, and available metadata from the test scenario phone call. The IVR tester may then save that test scenario and continue to the next scenario. The saved scenario may now be used automatically by the IVR test case generator for regression testing or duplicated and edited for use in other systems.

A system for flexible and scalable automated end-to-end chat-based contact center testing, having a test case management platform, a chat cruncher, a contact center manager, a chat classifier, a desktop automation engine, and headless browser-based virtual agents and customers. The test case management platform allows a user to configure operation of the system. The chat cruncher operates a plurality of virtual customers. The contact center manager operates a plurality of virtual agents to participate in chat session with virtual customers.

A system for flexible and scalable automated end-to-end chat-based contact center testing, having a test case management platform, a chat cruncher, a contact center manager, a chat classifier, a desktop automation engine, and headless browser-based virtual agents and customers. The test case management platform allows a user to configure operation of the system. The chat cruncher operates a plurality of virtual customers. The contact center manager operates a plurality of virtual agents to participate in chat session with virtual customers.

An artificial intelligence (“AI”) system for tuning a machine learning interactive voice response system is provided. The AI system may perform analysis of outputs generated by the machine learning models. The AI system may determine an expected model output for a given test input. The AI system may determine accuracy, precision and recall scores for an actual output garneted in response to the test input. The system may determine performance metrics for interim outputs generated by individual machine learning models within the interactive voice response system. The AI system may replace malfunctioning models with replacement models.

A system for flexible and scalable automated end-to-end chat-based contact center testing, having a test case management platform, a chat cruncher, a contact center manager, a chat classifier, a desktop automation engine, and headless browser-based virtual agents and customers. The test case management platform allows a user to configure operation of the system. The chat cruncher operates a plurality of virtual customers. The contact center manager operates a plurality of virtual agents to participate in chat session with virtual customers.

A system for flexible and scalable automated end-to-end chat-based contact center testing, having a test case management platform, a chat cruncher, a contact center manager, a chat classifier, a desktop automation engine, and headless browser-based virtual agents and customers. The test case management platform allows a user to configure operation of the system. The chat cruncher operates a plurality of virtual customers. The contact center manager operates a plurality of virtual agents to participate in chat session with virtual customers.

A communication normal-operation availability checking apparatus is provided for checking normal-operation availability of communications that go through a first network, a second network and a third network. The communication normal-operation availability checking apparatus includes: a list generation unit configured to generate a list including one or more carriers that provide a detectable first network; and a checking unit configured to check the normal-operation availability of the communications by executing a test that goes through the first network based on the list.

A system and method for testing of automated contact center customer response systems using a customer response testing system and a real time conversation engine, wherein the customer response testing system generates simulated human queries using persona profiles, sends test cases containing those queries to a contact center under test, and receives and analyzes the responses to determine whether the contact center's automated response systems understand the queries and respond appropriately.

A system and method for testing of automated contact center customer response systems using a customer response testing system and a real time conversation engine, wherein the customer response testing system generates simulated human queries using persona profiles, sends test cases containing those queries to a contact center under test, and receives and analyzes the responses to determine whether the contact center's automated response systems understand the queries and respond appropriately.