Business profile data
The platform stores business, website, onboarding, audit, content, and publishing context needed to operate SEO workflows.
Privacy
Privacy for the AI SEO workflow.
This privacy page restores the public legal route in the new Turborepo and should be finalized with counsel before production launch.
Data
business context
LLM
usage tracking
AWS
runtime controls
Privacy surface
Business, content, and publishing data
Business profile data
Protected
Generated content
Tracked
Publishing credentials
Secret
Usage events
Audited
Restored from the old public navigation and aligned with the new V2 route system.
What this page covers
Privacy Policy belongs in the same V2 public system as the rest of Uplift AI.
This route restores the previous seo-fe navigation surface while keeping the new Turborepo design consistent, brand-configured, and production-shaped.
Credential boundaries
Publishing credentials should live behind secure runtime boundaries such as AWS Secrets Manager or SSM.
Review before launch
This route is a production placeholder and should be reviewed with final legal policy language before public launch.
Workflow
Keep the page connected to real product operations.
The public page should point buyers into working auth, onboarding, audit, pricing, and dashboard paths while deeper detail pages are built.
1
Collect only needed data
Keep data collection scoped to onboarding, content, publishing, billing, and operations requirements.
2
Protect sensitive config
Load secrets from AWS-native boundaries instead of exposing them through client bundles.
3
Audit changes
Use audit trails and usage records to preserve operational visibility.
FAQ
Common questions about privacy policy.
Is this final legal copy?
No. This restores the route and page shell. Final privacy language should be approved before production launch.
Are secrets exposed on the client?
No. Client pages should only use public runtime config. Sensitive config belongs in server or AWS runtime boundaries.
Does the system track LLM usage?
Yes. LLM usage tracking is part of the planned production data model and reliability layer.
Continue
Move from public page to real workspace.
Start with signup, audit the business, and let the dashboard guide the next production workflow.