How Gnomeo uses AI
Gnomeo uses AI-assisted analysis to produce reports and recommendations from uploaded ad exports and workspace context. Customer workspaces remain private by default.
AI policy
AI & Product Improvement Policy
Gnomeo uses AI-assisted analysis to produce reports and may learn from aggregated, anonymized patterns, while keeping workspaces private and raw uploads out of public foundation-model training.
What may be used to improve the product
We may use aggregated, anonymized, and non-identifiable operational patterns to improve report quality, benchmarking, weak-signal detection, platform reliability, and operational insight.
Why limited aggregate learning helps
Broad non-identifiable patterns can make recommendations better over time without exposing customer names, client names, campaign names, or raw exports.
What we do not do
- We do not sell raw customer uploads.
- We do not publish customer data.
- We do not expose one workspace to another.
- We do not use raw uploads to train public foundation models.
Future controls
Future privacy controls may allow stricter opt-outs or immediate raw-deletion modes for customers that want the narrowest possible retention profile.
Product improvement policy
Gnomeo should stay affordable for small businesses and agencies, and the safest way to improve it over time is with limited aggregate learning rather than a raw-data warehouse.