No fake proof
MadeSimple.ai should not use invented testimonials, fake logos, fabricated awards, or ranking claims. If proof cannot be stated honestly, it should not be used.
Proof method
How MadeSimple.ai uses proof and case studies.
How MadeSimple.ai talks about savings, anonymised work, case studies, and proof without inventing claims or fake social proof.
Savings need a baseline
Operational savings should be tied to a workflow baseline: volume, time per task, error reduction, cost avoided, response speed, or another measurable business input.
Anonymised work stays clear
Some work cannot name the client or sector in detail. In those cases, the page should explain the pattern, what changed, and how the result was measured without exposing private information.
How to read anonymised results
An anonymised result should still explain the type of workflow, the operational baseline, the change made, and the measurement used. It should not imply a public endorsement, named client relationship, or guaranteed outcome unless that proof exists and can be shown.