EYZEC AI Checkup Preview
Check your AI.
Before the
next launch.
A clearer way to review a new model or a changing workflow. Set your expectations, test selected responses, and see what needs attention.
Start with one workflow. No Gateway installation needed.
Northline · Customer support
A clear view.
A practical next step.
Selected responses reviewed against a six-test plan.
- Tests
- 06
- Passed checks
- 04
- Findings
- 02
Review the findings before deciding what to change or test next.
A new model.
A reason to check.
A changed prompt.
A reason to check.
A new workflow.
A reason to check.
From uncertainty to a next step
Four steps. One useful report.
You define what matters. Checkup helps you keep the tests, responses, and review together.
Choose the workflow
Name the model and the task you want to review. Start small enough to understand the results.
Set the expectations
Choose or edit test questions. Define what a response should include, avoid, or send to a reviewer.
Review the responses
Record responses yourself or import a supported local test run. Review findings and anything requiring human judgment.
Decide what comes next
Download your report. Save the checkup and start a fresh revision when the model or workflow changes.
See the deliverable
A report your team
can actually use.
Start with the owner summary. Then look at the questions, responses, review notes, and test scope behind it.
Open the sample PDFFour pages. Fictional results, clearly labeled throughout.
Inside the report
- The overall picturePassed checks, findings, items awaiting review, run errors, and tests not run.
- The details behind itTest expectations, recorded responses, and reviewer notes.
- The decision to makeAn owner summary, test scope, and limits to keep the next conversation focused.
A passed check means a selected expectation was met. It is not an overall safety rating.
Your industry. Your expectations.
Bring the work your team knows.
Start with a text task and test cases your team can review. Industry labels organize the checkup; they do not supply specialist validation.
- Financial Services
- Healthcare
- Aviation & Aerospace
- Customer Support
- Human Resources
- Insurance
A few clear answers
Know what
you’re starting.
What can the first version check?
You can record text responses and apply exact-text, required-text, excluded-text, or JSON-format checks. Tests needing judgment can be assigned a manual review. The local runner supports selected OpenAI-compatible, non-streaming text connections; we confirm your connection before a walkthrough involving your model.
Does it run my whole AI application?
The first runner sends isolated test conversations to a model endpoint. It does not exercise your application’s full session, connected tools, voice, images, or downstream actions. You can also record responses manually, with their origin and context reviewed by your team.
How is this different from a Shadow Assessment?
AI Checkup reviews responses against a test plan you choose. A Shadow Assessment observes supported requests routed through the Gateway and reports their policy results. They answer different questions. Checkup does not require a Gateway installation or block live traffic.
Where does the information go?
The current Checkup app keeps your work in the browser session until you download it. Save your checkup before closing the page. With the optional local runner, test prompts go from your machine to the provider you select. Provider credentials stay out of the website and belong in the local runner’s environment. Use approved staging or synthetic information.
Does a passed check mean the AI is safe?
No. A check covers only its defined expectation and recorded response. Results and reviewer names are not independently authenticated. The report is not a certification, legal opinion, insurance policy, clinical validation, security guarantee, or guarantee of business outcomes.