AI & automation
Evaluation & guardrails
Test sets, output checks and limits, so you know how accurate the AI is.
What are AI evaluation and guardrails?
Evaluation is how you measure an AI feature: a test set of real questions with known answers, run before launch and after every change. Guardrails are the checks and limits that keep it on topic, catch bad output and cap usage, so you know how accurate the AI is instead of hoping.
What problem do evaluation and guardrails solve?
Without testing, there’s no way to know how often an AI feature is wrong, or whether last week’s change made it better or worse. Problems are found by customers, which is the most expensive way to find them.
An evaluation set turns accuracy into a number you can track. Guardrails stop the most likely failures, such as off-topic answers, made-up details or runaway usage, before they reach anyone.
What you get
A measured AI feature: an evaluation set, checks on every output and limits that keep it within scope.
Evaluation & guardrails
What’s included
Evaluation set
Real questions with known answers, including the hard ones.
Accuracy measurement
Results reported in plain terms, before launch.
Output checks
Filters that catch answers outside the rules before users see them.
Topic limits
The feature stays on the subjects you set and declines the rest.
Usage limits
Caps that keep costs and abuse under control.
Re-testing after changes
Run again after every significant change to prompts, models or content.
Who needs evaluation and guardrails
A good fit for
- AI features that reach customers. Where a wrong answer costs trust or money.
- Regulated or sensitive information. Where you need evidence the feature behaves.
- Teams improving an existing AI feature. To prove a change made it better, not just different.
Probably not the right fit if
- Staff use a general AI tool for drafting and check everything themselves.
- There’s no AI feature yet. Build it with evaluation from the start instead.
- You want a guarantee it’s never wrong. Testing measures and reduces errors; it can’t remove them.
How it works
How it works
- 01
Build the test set
Real questions with known answers, including the hard ones.
- 02
Measure
Accuracy reported before launch, in plain terms.
- 03
Guard
Checks and limits that stop problems reaching users.
How long does an AI evaluation take?
In our own builds, testing is part of the 2–6 week timeline: 20 past examples for automations and 50 real questions for assistants. Evaluating a feature someone else built depends on its size, and we confirm the timeline in your fixed quote.
How much do evaluation and guardrails cost?
They’re included in every assistant and automation we build. For a feature built by someone else, we quote a fixed price after a free 30-minute call.
Related work
Built and in production.
Questions
About evaluation & guardrails
Can you test an AI feature someone else built?
Yes. We can build an evaluation set for an existing feature and report how it performs, in plain terms.
How often should AI features be re-tested?
After every significant change to prompts, models or content, and on a regular schedule, because the underlying models change too.
What does an evaluation report show?
How many test questions the feature got right, where it went wrong and what kind of mistakes it makes, so you can decide whether it’s ready.
Can guardrails make an AI feature 100% accurate?
No. They reduce and catch errors, and evaluation tells you how often they still happen. For decisions that matter, keep a person reviewing the output.
Why do the AI models change?
Providers update and retire models over time. Re-running the evaluation after a model change shows whether accuracy held.
Further reading
AI & automation
More in AI & automation
- AI assistantsAssistants for customers or staff that answer from your own content and hand over to a person.
- Document search & retrievalAsk questions across your documents and get answers that cite the source.
- Workflow automationRemove repetitive steps: sorting enquiries, extracting details and updating systems.
- LLM integrationLanguage models added to an existing product or internal tool, with structured output.
- All of AI & automationThe full service, related work and questions.
Enquire
Talk to us about evaluation & guardrails.
Tell us what you are working on and what you need. An outline is enough to start. We reply within one business day.
Prefer email? hello@vareonhq.com