The Surveillance Capitalism Trap
I am a developer in recovery. When I looked for addiction recovery apps, I realized a disturbing trend: Most "free" tools sell behavioral profiles to advertisers or, in the worst cases, gambling networks. If you are quitting alcohol, you become a high-value lead for liquor advertisers. If you are quitting gambling, you are sold back to the platforms you're trying to escape.
I built LiftMind because I believe the user shouldn't be the product. Our goal is to offer "Smart" recovery tools without the surveillance baggage.
"You cannot leak what you do not collect. At LiftMind, we treat user data as a liability, not an asset."
The "Zero PII" Authentication Model
The core of our privacy model is simple: We do not know who you are. While most apps force you to sign in with Google, Facebook, or a phone number, we have eliminated the paper trail at the root level.
1. No Identity Required (No-KYC)
You register with just a username and a password. No email, no name, and no phone number are ever requested. Even if our database were leaked, there is zero personally identifiable information (PII) to link a user’s logs to their real-world identity.
2. Payment Privacy via Monero (XMR)
Financial records are often the weakest link in a "private" stack. To solve this, we accept Monero (XMR) for our premium tier. This allows for payment anonymity that matches our auth anonymity, ensuring your bank statement never reveals you are using a recovery service.
Architecture: The Blind AI Proxy
To provide pattern recognition and relapse prevention insights, we utilize SOTA Large Language Models. However, we do not let the AI provider see "You."
- The Calculator Model: We treat the external LLM like a calculator, not a database. We send it data for processing, but we never send identity.
- Metadata Stripping: Our custom Blind Proxy strips all metadata, IP addresses, and user identifiers before a request is sent. The LLM provider only sees a request coming from our server IP.
- Contractual Protection: We use the paid API tier, which contractually blocks the provider from using user data for model training. This is the same legal guarantee relied upon by banks and medical institutions.
Application-Level Encryption (AES-256-GCM)
For the data that must be stored, like daily journal entries and behavioral metrics, we utilize AES-256-GCM encryption before the data ever touches our disks. This ensures that sensitive mental health data remains decoupled from identity and is unreadable to anyone but the user.
Conclusion: Utility Without Compromise
LiftMind was engineered to solve a fundamental conflict in digital recovery: the need for high-level pattern recognition versus the necessity of absolute privacy. By integrating a SOTA (State-of-the-Art) reasoning model within a "Zero PII" framework, we have decoupled behavioral intelligence from personal identity. While standard recovery tools function as data-harvesting engines for advertisers, our stack is mathematically hostile to surveillance.