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AI Testing Service
Fully Managed QA for AI-Powered Apps
Verify the reliability and compliance of your AI solutions
We tailor our QA methodology to your needs to address the unique challenges of testing AI-powered products to ensure quality, safety, and ethical standards for your innovative solutions.
AI Software Testing Services We Provide
We offer a comprehensive approach: a combination of traditional and AI-tailored testing.
Our team excels at validating AI-driven applications by addressing the unique challenges of NL, LLMs, and deep learning systems. We combine traditional QA practices with specialized AI-focused techniques to ensure models perform reliably and ethically in production.
Functional testing
- Validation of API requests and responses (e.g., format, data validity) to verify correct data exchange with the AI service.
- Testing typical and edge cases (e.g., empty requests, long prompts) to ensure consistent system behavior.
Security Testing
- Verifying the API key protection and permission controls to prevent unauthorized access and data exposure.
- Testing for prompt injection risks (e.g., SQL, script injection) to verify the systems' robust security and resilience.
Integration Testing
- Verification of AI service connection (e.g., successful hand-shake, authentication, handling of 400/500 errors) to validate stable integration.
- Simulation of failure scenarios (e.g., timeouts, network errors) to verify fallback mechanisms work as expected.
Production Monitoring
- Tracking key metrics (e.g., error rates, latency, input data drift) to identify issues in real time.
- Checking alerts for threshold breaches to ensure a timely response to critical failures or slowdowns.
Production Monitoring
- Tracking key metrics (e.g., error rates, latency, input data drift) to identify issues in real time.
- Checking alerts for threshold breaches to ensure a timely response to critical failures or slowdowns.
Model Training Validation
- Checking whether the model is training correctly on the given data.
- Detecting overfitting or underfitting.
- Ensuring the quality and relevance of the training dataset.
Bias & Fairness Testing
- Identifying discriminatory or unfair outputs based on gender, race, age, or other attributes.
- Assessing data balance and AI responses for fairness.
Prediction Accuracy Testing
- Verifying whether the AI is correctly classifying, predicting, or making decisions.
A/B Testing of AI Behavior
- Comparing different AI model versions or logic to identify which one performs better.
Load and Stress Testing
- SLA testing for latency during high load (e.g., 100–1000 concurrent requests) to ensure system performance under pressure.
- Validation of request limits and throttling (rate limiting) to verify how the system handles overload.
We use advanced tools and proprietary methodologies to ensure maximum coverage and testing efficiency.
Learn more from our recent case studies.
Why choose QATestLab to Test AI Product
Tailored AI software testing process
QA methodologies will be adapted to your AI app’s unique logic, so you receive test coverage that is precise, reliable, and aligned with your product’s specific needs.
Ensuring ethical and secure AI behavior
Your AI product will be thoroughly validated in its critical behaviors before release, so it will be protected against reputational, legal, and ethical risks.
Fully managed skilled QA team
Through flexible, scalable delivery models, including fully managed teams, you will gain access to QA engineers with deep AI expertise, helping you maintain consistent quality across the AI testing process.
Comprehensive cross-environment validation
Your AI app will be tested on real devices, OS, browsers, and configurations, supported by our arsenal of 500+ physical devices, to confirm its performance and compatibility in real-world conditions.
AI-powered testing aligned with industry requirements
QA processes will be aligned with industry regulations, so your product passes audits faster, meets market requirements, and is ready to scale in regulated environments.
Quick AI software testing Start
You get a response within 1 day and a quick project start within 1–3 days after signing the documents to ensure your product will be ready to launch within your desired timeframe.
Ensure your AI product is ready for real-world conditions
Fill out the form, and we'll get back to you to suggest an AI testing approach tailored to your goals and timelines.
