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AI Agent Testing Service

Specialized QA for AI Agents - Comprehensive Testing Backed by Profound Expertise

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20+

years of experience

3000+

successful projects completed

250+

QA engineers
(Junior, Middle, Senior)

500+

real testing devices 

ensure reliability

Ensure the reliability and smooth performance of your AI agent

Our QA approach is tailored to address the unique challenges of AI-powered product testing to validate the reliability, accuracy, and overall quality of your AI agent.

AI Agent Testing Services We Provide

Our comprehensive approach: a combination of traditional and AI-tailored QA.

AI agents are more than just isolated algorithms – they are sophisticated systems equipped with their own memory and access to external tools. We combine the best practices of classical software testing with advanced AI validation methods to ensure thorough, end-to-end quality assurance.

Agent logic testing

  • Validation of goal and subtask planning mechanisms.
  • Testing the cycle: perception–decision–action feedback.

CI/CD for AI agents

  • Automation of the launch of lookup scripts after changes in planning logic or the model.

Functional testing of agent behavior

  • Simulation scenarios to verify task completion.
  • Validation of integrated tool usage (API requests, search, file operations).

Security and ethical testing

  • Restricting undesired behavior (if the agent executes code or makes purchases).
  • Testing for bias in the agent’s decisions across different user groups.

Stability testing during long-running sessions

  • Simulation of multi-turn queries with context accumulation.
  • Memory evaluation: verifying correct storage and retrieval of prior data.

Agent performance metrics evaluation

  • Measuring task success rate, time to complete, and number of steps.
  • Evaluation of resource usage (CPU and memory during extended sessions).

MCP Tools Connectivity

  • Checking connectivity among the MCP Server, Client, and Host.
  • Testing dynamic Tool Discovery via MCP metadata APIs.
  • Verifying secure context propagation and error-handling over MCP channels.
  • Enhancing observability to pinpoint bottlenecks in agent-to-tool interactions.

Multi-Agent Orchestration Testing

  • Execution of roles according to system instructions.
  • Validation of the dynamic role hand-off between agents in a processing chain.
  • Simulation of branching task sequences to verify correct agent selection.
  • End-to-end chain integrity checks across multiple agents.

Hallucinations and reasoning accuracy testing

  • Evaluation of responses to conflicting prompts (e.g., ambiguous or provocative queries).
  • Verifying logical conclusions (chain-of-thought auditing).
portfolio

We rely on proven tools and proprietary frameworks to achieve high test coverage and make the QA process faster and more efficient.

Learn more from our recent case studies.

Why choose QATestLab to Testing AI Agents?

Tailored agentic AI testing process

QA methodologies will be adjusted to address the unique challenges of AI agents, so you receive a testing strategy aligned with your product’s specific needs.

Swift start of AI agent testing

We provide prompt responses and fast start service, so your AI agent will be ready to launch within your desired timeframe. We can begin within 1–3 days after the documents are signed.

Fully managed skilled QA team

Through flexible, scalable delivery models, including fully managed teams, you will gain access to QA specialists with AI expertise to ensure consistent quality control tailored to your project.

Comprehensive cross-environment validation

Your AI agent will be tested on real devices and diverse configurations, supported by our arsenal of 500+ physical devices, to confirm its performance and compatibility in real-world conditions.

Agentic AI testing aligned with industry requirements

QA strategies will be tailored to industry-specific regulations, so your AI solution meets all market requirements and is ready to scale in regulated environments.

Ensuring ethical and secure AI agent behavior

Your AI agent will be assessed for fairness, bias, security vulnerabilities, and performance degradation to help reduce risks during deployment.

Make sure your AI agent works correctly and efficiently

Tell us about your product — we’ll review it and get back to you with a tailored testing approach and next steps.

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FAQ

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