AI Integration Testing (LLM & ML)

We ensure the predictability of AI in your product. We test AI features for hallucinations, prompt injections, and logic in handling non-standard requests. We guarantee safe user interaction with your algorithms and validate AI output quality.

What We Test

  • Hallucination detection and output accuracy testing
  • Prompt injection and jailbreak resistance testing
  • Edge case and adversarial input testing
  • Response consistency and quality validation
  • Bias and fairness evaluation
  • Fallback behavior and error handling checks

Tools & Technologies We Use

OpenAI PlaygroundLangChainCustom Prompt-Injection ScriptsPytestWeights & Biases

Our Process

1

Model Analysis

We study the intended behavior and guardrails of your AI

2

Adversarial Testing

We try to bypass safety filters and find edge cases

3

Prompt Evaluation

We test various inputs to ensure output stability and quality

4

Safety Report

You get a detailed audit of AI reliability and risks

Frequently Asked Questions

What types of AI systems do you test?

We test LLM-powered chatbots, AI assistants, recommendation engines, content generation tools, and any product with ML-based features. Our methodology covers both the AI logic and its integration with your application.

How do you test for prompt injections?

We use a comprehensive library of known attack patterns plus creative adversarial testing. We attempt to bypass system prompts, extract sensitive data, and manipulate AI behavior. Each vulnerability is documented with a severity rating.

Can you test AI features in production?

Yes, we can test in both staging and production environments. For production testing, we use carefully designed non-destructive test cases that simulate real user behavior without affecting your live data.