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Put your AI to the test.

Practical guides for testing models, understanding risk, and turning results into evidence you can review.

Start learningExplore use cases

From a question to a clearer decision.

Define the purpose. Examine the risks. Gather evidence. Learn how an Assessment brings the work together.

Get to know Assessments
An example Assessment in Knotest. Illustrative Project data.
An example Assessment in Knotest. Illustrative Project data.

One connected case, from purpose to follow-up.

Get to know Assessments
  1. 1Intent
  2. 2Risks
  3. 3Controls
  4. 4Testing & Evidence
  5. 5Decisions
  6. 6Confidence

Find out what holds up.

Keep the inputs clear, test the conditions that matter, and examine the examples behind a result. Build an evidence trail you can return to.

Explore Testing

What would you like to do?

Find a starting point for the work in front of you.

View all use cases

Review an AI system before a pilot

Build a case for a bounded use before deciding whether to proceed.

Assess risks

Inspect and correct Dataset labels

Turn quality findings into reviewed annotations and a new version.

Prepare data

Compare model candidates on the same question

Use a common Dataset and test basis to examine candidate differences.

Test models

Learning paths

Build your knowledge one useful workflow at a time.

All learning paths
Test models8 guides

Run your first evaluation

Take a concrete question from a Project to a reviewed result and report.

  1. Get Knotest
  2. Create and open a Project
  3. Import a Dataset
  4. Add and configure a Model
  5. Create a Test plan
  6. Prepare and run tests
  7. Read scores and inspect results
  8. Create and share a report
Follow this path
Assess risks7 guides

Build a case for an AI system

Follow the connected stages from intended use through a decision and later observations.

  1. Assessments
  2. Define the intent
  3. Record and examine risks
  4. Document controls
  5. Review testing and evidence
  6. Record a decision
  7. Maintain confidence after a decision
Follow this path

Collections

Explore connected workflows for a shared goal.

All collections

AI system review

Make the purpose, risks, evidence, and decision inspectable.

6 use cases

Data and connections

Build a clear input basis before asking a model for results.

6 use cases

Model evaluation

Ask a fair question and examine the measurements behind an answer.

6 use cases

Evidence and handoffs

Give the next person the finding, its basis, and the next action.

6 use cases

A little context goes a long way.

Understand the records behind your work, from reusable inputs to reviewed evidence.

Explore the documentation

Vault

Keep the inputs and files your Project reuses in one place.

Testing

Turn a saved question into a Run, result, and report.

Assessments

Build the case for a product version and a stated use.