AI Agent Simulations
Pressure-test your AI agent at scale before it ever talks to a real customer.
Run scenario-aware, auto-generated conversations in seconds to catch failures, validate changes, and ship with confidence.
Run scenario-aware, auto-generated conversations in seconds to catch failures, validate changes, and ship with confidence.
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TEST AT SCALE, SHIP WITH CONFIDENCE
Run dozens of end-to-end conversations in seconds, powered by a platform proven across hundreds of millions of real calls. Validate every prompt change, workflow update, and edge case in parallel so issues are caught early, not in production. Built for complex, high-stakes customer conversations, Simulations helps ensure your agent performs with consistency and quality across every scenario.
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Your Partner in AI Agent Testing
Simulations is part of a complete testing suite built for real-world deployment. Regal’s Forward Deployed Engineers partner with you to validate conversational logic, voice quality, and pronunciation, combining automated and hands-on testing to ensure your agent is ready for production.
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frequently Asked Questions
How do Regal Simulations work?
Regal Simulations use AI to simulate full conversations between your AI agent and an AI-generated customer. Test cases are created from your prompts, workflows, and guardrails, then run end-to-end in bulk and evaluated by LLMs against success criteria you define. The result: clear pass/fail outcomes, full transcripts, and confidence your agent performs across the scenarios that matter.
What kinds of issues can Simulations uncover?
Simulations help teams catch issues across conversational logic, objection handling, retrieval performance, unsupported requests, action invocation, and brand or compliance guardrails. It is especially useful for identifying failures in edge cases, multi-turn conversations, and other non-deterministic scenarios that are difficult to cover with manual role-play alone.
How are Simulations different from manual QA?
Manual QA is slow, inconsistent, and difficult to scale across complex AI agent deployments. It also can’t realistically reproduce the variability of real customer behavior, from unexpected objections to multi-turn, off-script conversations. Simulations lets you auto-generate diverse, scenario-aware test cases, run them in bulk, and re-run them whenever prompts or knowledge bases change. That means broader coverage across real-world conversation paths, faster iteration cycles, and less risk of broken experiences reaching live customers.
Can Simulations be used for regression testing?
Yes. Simulations are designed to support continuous regression testing for AI agents. As your prompts, workflows, and knowledge bases evolve, you can regenerate and rerun test suites to confirm that new changes did not break existing flows. This makes it much easier to ship improvements while maintaining confidence in performance.
What does the testing process look like?
Regal works with your team to identify the highest-priority conversation flows, configure test coverage, and align simulations to your prompts, workflows, and success criteria. In addition to the self-serve platform, you’ll be supported by a Forward Deployed Engineer with expertise in prompt design, context engineering, and evaluation frameworks to help your team launch faster and improve over time.
Do you train your models on my customers’ data?
No. Regal does not train proprietary models on customer data. We securely integrate with trusted LLM providers such as OpenAI, Anthropic, and Gemini under agreements that explicitly prohibit training on your data. All customer information remains private and protected.
