Gen AI application testing services

Our Gen AI application testing services ensure that your solutions—from AI chatbots to fully autonomous agents—are functional, resistant to adversarial attacks, and scalable in real-world scenarios. Move from “cool prototype” to “production-ready” with ITRex.

What is the scope of our Gen AI application testing services?

Traditional QA isn't enough for nondeterministic software. We combine our engineering heritage with AI-native testing and frameworks to validate the "last mile" of your AI product—the application layer where users interact and risks emerge. Our generative AI testing services cover:

Functional testing

When testing generative AI applications, ITRex validates that the models perform their intended functions within the context of your business logic:

Prompt & response validation. We verify that Gen AI models handle prompts correctly and produce desired outputs while also checking the content for relevance, coherence, and tone.
End-to-end UI/API interactions. We test the full user journey, ensuring seamless SLM and LLM integration with your UI and back-end APIs without breaking workflows.
RAG accuracy. We validate your retrieval-augmented generation (RAG) pipeline against specific RAGAS metrics (faithfulness, answer relevance, and context precision) to ensure that the model produces context-aware answers grounded on your data.

Security & safety testing

As part of Gen AI application testing, ITRex proactively safeguards your models against evolving threats, manipulation, and unauthorized data exposure:

Adversarial simulation (red teaming). We simulate real-world attacks and edge cases to protect your system from prompt injection, “jailbreaking,” and attempts to bypass safety filters.
Data leakage prevention. We examine model outputs and logging mechanisms to prevent the application from unintentionally revealing PII, proprietary code, or sensitive training data.
Safety filter validation. We stress-test your Gen AI guardrails to validate they effectively block toxic, harmful, or inappropriate content, aligning your AI’s behavior with corporate compliance standards.

Performance & scalability testing

One of the goals of ITRex’s generative AI testing services is to ensure your apps deliver consistent performance and cost-efficiency, even under peak user loads:

Load & stress testing. We monitor Gen AI’s response time (latency) and system stability during high concurrency to avoid timeouts and ensure your infrastructure scales smoothly.
Resource & token usage optimization. We analyze throughput and token consumption patterns to identify inefficiencies, helping you predict operational expenses and streamline your LLMOps pipelines.
Comparative model benchmarking. We evaluate different foundation models (LLMs vs. SLMs) against your performance baselines, helping you select the architecture that balances latency, quality, and infrastructure costs.

Why do specialized Gen AI application testing services matter?

As Gen AI permeates software products, new risks emerge that traditional testing cannot detect. Partnering with our Gen AI application testing company guarantees you:

Prevent "hallucinations" & liability
An LLM-based healthcare assistant "hallucinating" a nonexistent drug interaction could jeopardize patient safety and have serious regulatory ramifications. With ITRex’s generative AI QA services, you can stop your application from confidently stating such falsehoods, protecting your brand’s reputation and avoiding legal penalties.

Block new threat vectors
A manipulated input may trick your enterprise agentic system into disclosing executive salary information or confidential trade secrets to an unauthorized employee. Our Gen AI testing experts proactively safeguard your software against such prompt injections and "jailbreaks," ensuring your agent's logic cannot be hijacked and your sensitive data remains secure.

Control operational costs
Without optimization, scaling a customer support bot can result in massive cloud costs, while overlooked data issues may force expensive model retraining or trigger regulatory fines. Our generative AI testing identifies token inefficiencies and compliance risks early, helping you control operational spending, avoid costly rework, and mitigate financial liability.

Ensure user trust
A single instance of your AI producing biased, offensive, or politically charged content can quickly go viral on social media, eroding years of customer loyalty. Our Gen AI application testing services rigorously validate your model's output against safety filters and brand guidelines so that it consistently provides an ethical and on-brand user experience.

How do we approach Gen AI application testing?

We combine high-speed automation testing frameworks with critical human insight to validate the finer details that algorithms alone frequently overlook. Our generative AI application testing service is built around this hybrid approach, which keeps your solution scalable, quick, safe, and compliant.

Automated evaluation

Our Gen AI testing experts utilize “LLM-as-a-judge” frameworks to grade output quality at scale, checking for relevance and correctness. This allows us to check thousands of prompt variations in minutes, giving you rapid feedback on model performance without slow and costly manual reviews.

Adversarial red teaming

ITRex’s Gen AI security testing team proactively attempts to “break” your app using sophisticated injection libraries and social engineering tactics. By simulating these real-world attacks before deployment, we expose and patch hidden vulnerabilities so your AI doesn’t fall victim to malicious actors in the wild.

Human-in-the-Loop (HITL)

Our Gen AI application testing specialists provide the final layer of validation that automated tools may miss, including nuance, tone, and complex reasoning. With our help, your Gen AI solution can handle delicate subjects with the right amount of tact, reason, and safety while capturing the subtleties of your brand voice.

Reliable tech stack

As an experienced Gen AI testing company, we create our own pipelines using best-in-class open-source frameworks (LangSmith, TruLens, Ragas, and PyTest) and OWASP security guidelines. This flexible, non-proprietary method avoids vendor lock-in while offering strict quality control and smooth integration into your current CI/CD flows.

What is our experience with Gen AI testing?

Gen AI chatbot for REDI: simplified access to cancer information →

A Gen AI chatbot that uses Claude 3.5 to answer sensitive questions about cancer symptoms. ITRex performed rigorous safety testing and expert prompt engineering to define the AI's tone and behavior. We validated that the bot refused to provide medical diagnoses while remaining empathetic and helpful.

Gen AI sales training platform with a RAG architecture →

A SaaS solution that reduces sales rep onboarding time by 92% through automated, personalized course creation. ITRex performed extensive RAG accuracy testing and latency benchmarking to eliminate hallucinations. We validated the retrieval logic to ensure the AI delivered factually consistent, real-time responses.

Melody Sage: a Gen AI music learning platform →

An autonomous Gen AI tutor that creates personalized music curricula and conducts real-time consultations. ITRex used "LLM-as-a-Judge" systems to evaluate lesson quality and the agent's ability to reflect independently while minimizing latency and infrastructure costs.

Why collaborate with our Gen AI testing team?

AI-native DNA & deep QA heritage. We fuse 16+ years of manual and automated testing expertise with Gen AI consulting know-how. We don’t merely offer generative AI testing services—we build artificial intelligence. This skill set allows us to look past surface-level outputs and validate the internal architecture of your AI agents and RAG systems.

Security & compliance by design. Navigating regulations like HIPAA, GDPR, and the EU AI Act requires more than standard security scans. Our Gen AI testing frameworks specifically target AI-unique vulnerabilities—think adversarial robustness, model inversion, and statistical bias.

Continuous quality & integration. ITRex treats Gen AI testing as a continuous process, not a one-time event. By adding quality checks and automatic feedback directly into your CI/CD pipeline (QAOps), we make sure your AI models improve and grow without losing speed or quality in your releases.

End-to-end strategic partnership. Our generative AI QA team supports you from the initial AI PoC phase through to post-launch monitoring. Whether you need to validate a single prompt or manage a complex, enterprise-grade agentic ecosystem, we can help you bridge the gap between experimental pilots and stable, production-ready code.

Gen AI application testing FAQs

Think of traditional software like an accounting system: it follows strict rules where $1 + $1 must always equal $2. If you click “Checkout,” the cart total must update correctly every time. Testing is simple: did it work, or did it break?

Gen AI app testing is more like training a new customer service agent. If a user says, “I’m frustrated with your service,” the AI might apologize in five different ways. None are “wrong” in code, but some might be rude, off-brand, or factually incorrect.

As a generative AI testing company, we don’t just check if the software crashes; we test its behavior:

Traditional test: “Did the chatbot load?” (Pass/Fail)
Gen AI test: “Did the chatbot de-escalate the angry customer, or did it promise a refund we don’t offer?” (Nuance & Safety)

In other words, Gen AI application testing services ensure that your AI is a safe, accurate brand ambassador, not just working code.

Here at ITRex we use a hybrid Gen AI application testing strategy. We combine automated evaluation frameworks (using “LLM-as-a-Judge” to grade thousands of interactions) with human-in-the-loop validation to capture nuance. This includes functional testing of the API and UI layers, adversarial “red teaming” to simulate attacks, and performance testing to determine latency and token costs under load.

Hallucinations occur when Gen AI confidently asserts false or non-existent information as fact in response to user queries. To prevent this, we focus on generative AI app testing techniques specific to RAG architectures.

We verify whether the model is accurately retrieving context from your knowledge base and “grounding” its answers in that data. ITRex uses metrics like “faithfulness” and “answer relevance” to flag instances where the AI creates information not supported by the source text.

Achieving consistency in nondeterministic systems is a core challenge of testing generative AI applications. We tackle this by implementing semantic similarity checks—measuring how closely a new response matches a verified “golden reference” answer. Our team also validates temperature settings and system prompts to ensure that, while the phrasing may change, the fundamental logic, facts, and tone remain consistent across user sessions.

ITRex utilizes exploratory testing and Gen AI model testing techniques to detect statistical disparities across different demographics (e.g., race, gender). We conduct red teaming exercises where we intentionally try to provoke the AI into generating offensive or biased content. We then use these findings to calibrate your guardrails, keeping your application compliant and your brand reputation intact.

Standard metrics like “uptime” aren’t enough. In our generative AI application testing, we use a combination of quantitative and qualitative metrics.

Performance metrics: Latency (time to first token), throughput, and error rates
Quality metrics: RAGAS scores (faithfulness, context precision), BLEU/ROUGE scores for text similarity, and semantic coherence
Safety metrics: Success rate of prompt injection attacks and toxicity scores

This data replaces subjective guesswork with facts, giving you the confidence to launch a tool that is cost-effective, safe, and actually useful to your customers.

We turn complex regulations into concrete testing scenarios. For privacy laws like HIPAA and GDPR, we stress-test your application to ensure it never accidentally leaks sensitive user data. For the EU AI Act, we verify that your AI’s decision-making is transparent and traceable, so you have the hard evidence needed to pass safety audits. This comprehensive Gen AI testing coverage protects your business from legal risks and accelerates your approval process in regulated markets.