“We test the AI on a few examples and hope.”
Rare failures reach customers.
AI Quality Assurance Services
Demos look great. Real users ask real, messy questions. Our reviewers test your AI’s answers against clear criteria and tell you exactly where it goes wrong, so you can fix it before customers notice.
Prompt“Can I take ibuprofen with my blood pressure pills?”
Accuracy70%
Safety40%
Tone92%
Completeness65%
Error: missing safety advice Route to policy owner
You cannot fix what you have not measured
“Different people judge the answers differently.”
Results cannot be compared from one release to the next.
“We do not know what to fix first.”
The team works on what is easy, not what is serious.
We test with a written method, score consistently and give you a ranked list of what to fix.
Seven ways an AI answer can fail
Accuracy
Is it true?
Relevance
Does it answer the question?
Completeness
Is anything important missing?
Tone
Does it sound like your brand?
Policy
Does it follow your rules?
Safety
Could it cause harm?
Consistency
Same question, same answer?
Your criteria
Anything else you care about.
From test plan to action list
- Step 1
Agree the criteria
What does a good answer look like? We write it down with examples.
- Step 2
Pick the sample
Choose real or test prompts that cover your main use cases.
- Step 3
Train and calibrate
Reviewers score practice items until they agree.
- Step 4
Score and report
Scores, error types and real examples, ready for your team.
Know what to fix first
We don’t just give you a score. We group every error by type, show real examples and rank the problems by how often they happen and how much harm they could do.
Issues found per 1,000 outputsImproving
Wrong facts45%
Off-policy25%
Tone30%
How we test an AI system
- Step 1
Agree the failure types
Wrong facts, unsafe answers, tone, refusals and others, ranked by risk for you.
Test plan
- Step 2
Build the test set
Realistic and tricky prompts, including cases from your own users.
Test set
- Step 3
Score every answer
Reviewers use the same scale, and disagreements are resolved by a lead.
Scored results
- Step 4
Rank the fixes
Failures are grouped by cause and severity.
Action list
Timings depend on volume and complexity. We agree them with you in writing before the pilot starts.
How we keep testing repeatable
Written scoring scaleEveryone uses the same definitions.
Fixed test setThe same set is rerun after each change so you see real progress.
Reviewer agreementWe report how often reviewers agree.
Severity rankingA short list of what to fix first.
Who benefits on your side
AI engineers
Evidence of what fails, with examples.
Product owner
A release decision based on measured quality.
Risk owner
A record of what was tested before launch.
Questions buyers ask before they sign
Still have a question? Ask us directly.
Do you certify that our AI is safe?
No. We run operational tests and report the results. We are not an auditor or certifier.
How often should we test?
Before each significant release, and on a schedule for live systems. We suggest a rhythm after the first cycle.
Ready to build better operations
Tell us what you need to run, fix, or growWe will map out the right team and a pilot plan