Draft — pending final legal review.This page describes OORT's actual behavior as accurately as this team can write it, but it has not been reviewed or approved by counsel and is not yet a binding legal document.

AI & Modeled-Intelligence Disclosure

How OORT actually generates content

OORT's Recognition Engine, Activation Engine, and Optimization Engine are deterministic, rule-based systems — the same input always produces the same output. They are not powered by a large language model making open-ended claims; every value they produce traces back to either (a) something you typed, (b) category-pattern logic written into the product, or (c) a real, recorded metric.

Every number is labeled

Throughout the product you will see one of these disclosures attached to data:

What OORT does not claim

Attribution confidence

Where OORT connects an outcome to a campaign, it classifies the strength of that connection (Strong, Supported, Partial, Correlated, Modeled, or Insufficient evidence) rather than presenting every connection as equally certain. It never treats an impression, a click alone, geographic proximity, or timing overlap as proof that a specific outcome happened because of a specific campaign.