The Problems We Fix
"It gives confident answers that are wrong."
There is no check tying each claim back to a source. We test grounding at the claim level, not the response level.
"It answered differently the second time."
Output is sampled, not computed. We run the same and paraphrased prompts repeatedly and measure variance against an agreed threshold.
"The vendor updated the model and something broke."
Hosted models change without your code changing. Versioned baseline suites make that shift visible before release.
"One prompt tweak changed behavior everywhere."
Prompts are untested configuration running in production. We treat every prompt edit as a regression trigger.
"It pulled the wrong document."
Stale index, weak chunking, or poor retrieval ranking. We test retrieval separately from generation, so the fix is obvious.
What We Test
Accuracy & Relevance
Factual correctness, completeness, and response relevance.
Hallucination Testing
Detect unsupported or fabricated claims and trace responses to source data and context.
Prompt Testing
Test ambiguity, paraphrasing, typos, conflicting instructions, adversarial prompts, and out-of-scope requests.
Bias & Fairness
Compare responses across demographic and contextual variations for unfair differences.
Reliability & Consistency
Test repeated and equivalent prompts for unacceptable output variations.
Guardrail Testing
Verify that safety controls block harmful requests without unnecessarily blocking legitimate ones.
Make Your LLM Application More Reliable
PrimeQA tests your application for accuracy, reliability, safety, security, and performance, helping you catch issues before they reach users.
Our LLM Testing Methodology
Assess
Map your models, prompts, RAG pipeline, tools, guardrails, and dependencies.
Our LLM Testing Services
LLM Accuracy Testing
Correctness measured against curated ground truth datasets.
LLM Evaluation and Validation
Metric definition, scoring frameworks, and quality scorecards.
LLM Hallucination Testing
Claim-level grounding checks and fabrication detection.
Prompt Testing
Robustness across paraphrase, ambiguity, and adversarial phrasing
LLM Guardrail Testing
Enforcement and over-blocking verification.
AI Red Teaming
Structured adversarial testing of the full application.
How We Measure LLM Quality
Accuracy
Relevance
Faithfulness
Groundedness
Completeness
Coherence
Consistency
Hallucination rate
Toxicity
Bias indicators
Latency
Token consumption
The Testing Framework
Testing only the final answer tells you something broke, not where. We evaluate at every stage.
Standard LLM application:
Input → Prompt → Model → Tools and Retrieval → Output → Evaluation → Decision
RAG application:
Query → Retrieval → Context → Prompt → LLM → Response → Evaluation
Agentic system:
Goal → Planning → Tool Selection → Execution → Observation → Next Action → Response
Tools and Technologies We use
Download Free Software Testing Report Templates
Access a complete collection of software testing reports and templates for every QA phase.
- 20+ ready-to-use QA report templates
- Covers functional, automation, API, performance, security & mobile testing
- Fully customizable for your projects
Inside Our AI Testing Approach: A Real-World Case Studies
Semantic Testing of GroBro’s AI Chatbot
See how GroBro tested its AI chatbot using Selenium, Pytest-BDD, embeddings, and semantic similarity to validate dynamic responses.
25
Prompts Tested
60%
Semantic Similarity Threshold
100%
Automated Response Validation
2-Layer
UI + Semantic Testing
How AI Chatbots Navigate Localization and Regulatory Hurdles
Explore how PrimeQA Solutions delivers automation testing for chatbots and virtual assistants, ensuring seamless performance, accuracy.
40%
Improved Stability
35%
Fewer Critical Defects
100%
Milestone Adherence
2x
Faster Issue Resolution
Validating AI-Driven Business Intelligence Analytics Platform for a Shopify Merchants
How PrimeQA Tested LLM-Powered Recommendations for Accuracy, Reliability, and Business Alignment
17
AI Problem Statements
200+
AI Test Cases
150+
APIs Tested
1+
Year QA Engagement
What You Receive
Get a complete LLM testing package tailored to your architecture, use case, and risk profile, including:
LLM test strategy and detailed test cases
Prompt, adversarial, and injection test suites
Curated test datasets and evaluation criteria
Automated test scripts and evaluation frameworks
Hallucination, security, and safety findings
Regression and performance reports
Detailed defect reports with traceable evidence
Per-release AI quality scorecards
Prioritized recommendations for prompts, RAG, and guardrails
CI/CD integration guidance for continuous LLM evaluation
Why PrimeQA
Independent QA Expertise
Unbiased testing backed by proven test strategy, coverage, and defect management.
AI Testing Experience
Experience testing LLM applications, RAG pipelines, model migrations, and AI-generated recommendations.
Automation-First Approach
Automated evaluation frameworks and CI/CD quality gates for repeatable testing.
Engineering Depth
We analyze code, prompts, APIs, and integrations to provide actionable root-cause insights.
Experienced QA Team
QA engineers with 5+ years of average experience across functional, automation, API, performance, security, and AI testing.
Choose the Engagement Model That Fits Your Project
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Partner with PrimeQA to build a scalable QA strategy tailored to your industry. Tell us about your project and we'll get back within one business day.
- Free 30-minute discovery call
- Custom testing strategy included
- No commitment required