Independent thinking. Traceable evidence.
Evaluate AI
without the
sales pitch.
Define the use case, document the evidence and compare systems against the requirements that actually matter.
A working concept workspace. Fictional systems. No live model testing.
Evaluation record / illustrative
Evidence before endorsement.
Fictional demonstration. Status describes an evidence gap, not an AI system’s quality.
The evaluation discipline
A decision you can explain.
Start with the work.
Define the objective, data sensitivity and critical constraints before comparing a product.
Define a use caseKeep claims accountable.
Link each claim to a source, date, test result and reviewer note. Make missing evidence visible.
Open the evidence registerTake better questions forward.
Create a report of requirements, coverage, testing gaps and unresolved commercial questions.
Prepare a reportDesigned for consequential purchases
For the people who have to stand behind the decision.
CIOs, procurement teams, boards, security reviewers and professional services firms need a defensible process, not a universal leaderboard.
The workspace makes the limits of the evidence part of the evaluation.
Discuss an enterprise pilot