NiCE has announced the launch of its new tool, Cognigy Simulator.
The solution is designed to help enterprises evaluate, test, deploy, and scale production-grade AI agents used in CX operations.
Released via its Cognigy division, the tool allows enterprises to test out AI agents before deployment, by creating controlled simulations of realistic customer interactions, enterprises can evaluate how the agents respond.
Cognigy Simulator aims to reduce risk and build enterprise confidence in a controlled setting before exposing an AI agent in customer operations.
Philipp Heltewig, General Manager, NiCE Cognigy and Chief AI Officer, explained how the simulator will enable organizations to evaluate an AI agent’s readiness for real-world use.
“AI Agents have become a catalyst for transforming customer experience operations,” he said.
“Simulator provides data-informed testing and reporting to help organizations understand AI Agent performance and compliance alignment, so organizations can make deployment decisions with confidence.”
Simulating AI Agent Readiness
Testing AI agents with manual test or small samples is no longer enough evidence for confident deployment.
Operating as a software tool for testing and evaluating AI agents, Cognigy Simulator allows for large-scale experimentation before they’re deployed into real environments.
This includes allowing organizations to run multiple simulated user interactions with an AI agent to see how it performs with customers.
By providing evidence about how an AI agent behaves in real-world conditions, including realistic, unlikely, or unusual scenarios, this will allow enterprises to evaluate the agent’s capability to meet business goals and compliance requirements.
“AI-driven customer service is already entering a phase where ongoing evaluation and refinement are essential,” Heltewig added.
“Simulator integrates continuous testing directly into CX operations, ensuring AI Agents are routinely exercised, measured, and improved across build, deploy, and optimization cycles.”
By replicating real users for simulated use, Cognigy Simulator utilizes their data to represent different types of customers with varied demographics, intentions, and behaviors.
These synthetic customers can interact with the AI agent inside the simulation, revealing further information about strengths and weaknesses that a simpler scripted test might have missed.
Enterprises can launch thousands of interactions at once, speeding up deployment while ensuring an agent’s capability to handle a system.
This also includes simulations to be run on demand, scheduled regularly, or used in automated regression tests.
These interaction tests can include evaluating an AI agent’s: task completion rates, adherence to safety and guardrails, reliability of integrated systems and APIs, and overall experience quality for the user simulation.
Furthermore, the tool can run comparisons between different agent versions, prompting strategies, or system configurations to find the most effective setup.
Cognigy Simulator can also emulate various third-party responses from external APIs, including error conditions, to ensure an AI agent can handle integration points reliably.
The simulator can also cover voice and digital channels and test integrations such as CRM or backend systems.
As agents behave differently across channels, the simulator can run the same intent or scenario across voice and digital environments, exposing channel-specific issues such as misrecognition or unclear instructions.
These test scenarios provide quantitative data on agent performance rather than solely qualitative impressions.
By applying a scalable, evidence-based approach to testing AI agents before deployments through synthetic interactions, measurable criteria, and automated scenario generation, this helps organizations uncover AI flaws, measure performance, and improve quality within a controlled environment.
Strengthening AI-Driven CX
By allowing organizations to pre-examine an AI agent’s potential across thousands of potential interactions, this exposes probabilistic behaviour from LLMs and allows teams to tighten guardrails and reduce randomness.
Cognigy Simulator can also identify failure cases before customers encounter them, including missed intents, incorrect assumptions, and looping dialogs in a controlled setting.
This ensures consistent performance levels whilst allowing real customers to experience fewer errors, clearer answers, and more predictable outcomes.
By simulating real customer intents and behaviors, CX teams can measure whether customers are actually achieving their journey goals, enabling agents to support improvements in containment, resolution rates, and first contact success.
Cognigy Simulator also reveals issues such as unnecessary handoffs to help reduce friction in conversations; by fixing these issues before deployment, this leads to shorter interactions and lower customer effort.
It also tests rare and unusual behaviors to improve how an AI agent responds to unexpected inputs, emotional language, or incomplete information, protecting the customer experience in various situations.
Repeated and automated testing can allow CX teams to validate changes to prompts, flows, or models quickly, reducing the risk of degrading the experiences during updates.
Cognigy Simulator can also test multiple channels and integrations together, highlighting the gaps between design intent and actual behavior.
This means that CX teams can verify that a customer who switches from chat to voice can experience continuity rather than repetition or confusion, resulting in fewer dead ends and clear explanations when systems are unavailable.
Cognigy Simulator improves customer experience by reducing overall operational and experience risk, increasing reliability across channels and systems, and enabling continuous, measurable improvement of AI-driven interactions.
It ensures that AI agents are tested, stable, and aligned with customer expectations before and after they reach production.
To find out more about NiCE’s acquisition of Cognigy, check out this article today.
