#1 Agent to Agent Testing Platform

A unified platform to test AI agents, including chatbots, voice assistants and phone caller agent across real-world scenarios for key metrics such as bias, toxicity, hallucination and more.

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A unified platform to test AI agents, including chatbots, voice assistants and phone caller agent across real-world scenarios for key metrics such as bias, toxicity, hallucination and more.
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An AI Agent for Testing AI Agents

Testing AI agents from an end-user perspective requires accuracy, performance, and reliability. Since the behaviour of AI agents is super dynamic, there is a lot of confusion as to what to test. Here are a few key metrics that you could get insights on including:

  • Bias
  • Toxicity
  • Hallucinations and more

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An AI Agent for Testing AI Agents

Test AI-powered Chat, Voice, or Calling Agents

Automated scenario generation creates diverse test cases for AI agents simulating chat, voice, hybrid or phone caller interactions.

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Test AI-powered Chat, Voice, or Calling Agents

True Multi-Modal Understanding

Go beyond text! Define detail requirements, or upload PRDs of diverse inputs like images, audio, and video to help gauge expected output of the agent under test mirroring real-world scenarios.

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Agent to Agent Testing Platform

Autonomous Test Scenario Generation

Access 15+ swarms of agents to help judge the agent under test including:

  • Personality tone agent
  • Data privacy agent
  • Intent recognition agent and more

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Agentic Testing Platform

Diverse Persona Testing To Help Test Like Real Human

Leverage a variety of personas to simulate different end-user behaviors, needs, and interactions during testing. By using multiple personas such as International Caller, Digital Novice and more, ensure AI agent performs effectively for diverse user types.

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Diverse Persona Testing

Autonomous Testing at Scale with Synthetic End-Users

Get a detailed analysis for the agent under test, from the perspective of a synthetic end-user on key metrics such as Effectiveness and Accuracy, Empathy and Professionalism, and more, ensuring consistent intent, tone, and reasoning.

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Autonomous Testing at Scale with Synthetic End-Users

Regression Testing with Risk Scoring

Perform end to end regression testing for agent under test with insights into risk scoring that highlights potential areas of concern, allowing you to prioritize critical issues and optimize your testing efforts.

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Regression Testing with Risk Scoring

Seamless Integration with HyperExecute

Our platform seamlessly integrates with LambdaTest’s HyperExecute for large-scale cloud execution. Generate test scenarios and run them at scale with minimal setup, delivering actionable feedback in minutes.

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HyperExecute

What to Test Your AI Agents for?

Execute comprehensive operational testing for your AI agents with deep visibility into business metrics, conversational flow, and interaction dynamics. Intelligent scoring surfaces high-impact issues in talk ratios and handoff points, enabling you to optimize performance and ensure seamless transitions.

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What to Test

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Frequently Asked Questions

What is agent to agent testing?
Agent-to-agent testing refers to a testing approach where two or more AI agents interact with each other in a controlled environment to simulate real-world scenarios. This type of testing is used to evaluate how AI systems or agents, such as chatbots or virtual assistants, perform when they communicate or work together. The goal is to test their ability to understand, react to, and collaborate with each other in complex, dynamic environments, ensuring they can operate effectively in various use cases.
What is a testing agent?
An agent is a software component or module that functions autonomously to carry out specific testing tasks. These tasks may involve executing test scripts, gathering data, and generating reports.
What is agentic testing?
Agentic testing leverages autonomous AI agents to autonomously generate, execute, and refine tests throughout the entire software testing lifecycle.
What are the tech stack powering these AI capabilities for Agent-to-Agent Testing? Are these your or third-party models?
The AI capabilities are powered by a combination of third-party models and a sophisticated in-house agentic framework. Core AI Models: The system is primarily built upon multiple large language models (LLMs). The agents use these models for their core reasoning and generation tasks.
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