Persona Protocol
Developer PortalUser PortalTokenomics
  • Learn
  • Building Apps
  • Ecosystem
  • Users Hub
  • Introduction
    • What is Persona?
    • Use Cases & Applications
    • For AI Agents
    • Whitepaper & Technical Resources
    • FAQs
  • Protocol Overview
    • System Architecture
    • Protocol Components
      • Data Ingestion Engine (DIE) / Ingestion Layer
      • Trusted Execution Cluster (TEC) / Compute Layer
      • Secure Access Management (SAM)
      • Encrypted Storage Service (ESS) / Storage Layer
    • Security Implementations
    • A detailed example on how it works
Powered by GitBook
On this page
  • AI’s Missing Piece: You
  • How Persona Fixes This
  • Real-World Examples
  • Why This Works Now
  1. Introduction

For AI Agents

Today, users are forced to choose between privacy and personalization. We reject that binary.

AI’s Missing Piece: You

(Without Violating Your Privacy)

The Problem with “Personal” AI Today Your iPhone knows your routines. ChatGPT knows Wikipedia. But true personal AI—the kind that books flights aligned with your budget, avoids restaurants you’re allergic to, or drafts emails in your voice—doesn’t exist yet. Why?

Today’s Broken Tradeoff:

  • Option 1: Share raw data (e.g., bank statements, health records) → Get personalization but lose privacy.

  • Option 2: Keep data locked → Get generic, often useless AI.

Apple’s “Personal Intelligence” can’t escape this trap. Even their on-device AI lacks cross-app context (your Uber rides, your WhatsApp convos, your Fitbit data).

How Persona Fixes This

Privacy-Preserving Context Persona lets AI understand you without accessing you.

  1. Your Data Stays Encrypted

    • AI models never see raw data. Instead, they interact with encrypted context:

      • Example: A diabetes coach AI analyzes encrypted glucose levels from your Freestyle Libre sensor → Suggests meals without knowing your name, location, or medical history.

  2. Zero-Knowledge Personalization

    • Prove traits about yourself without exposing details:

      • “I have a seafood allergy” → Proven via ZK proofs from hospital records.

      • “I prefer business-class flights under $2k” → Derived from encrypted travel logs.

  3. AGI’s Privacy Layer Even superhuman AI needs your context to serve you. Persona ensures:

    • Training stays on public data (as it always will).

    • Inference (personalization) uses your encrypted data → Like giving ChatGPT a USB drive it can read but not copy.

Real-World Examples

  1. Healthcare AI That Actually Cares

    1. Share encrypted sleep patterns (Oura Ring) + work calendar (Google) with a burnout-prevention AI → Gets “Reduce meetings after poor sleep” alerts → Never sees raw event titles or biometrics.

  2. Truly Private Shopping Assistants

    1. Prove you’re a “size 8 shoe buyer with $200/month budget” to an AI stylist → Gets Nike recommendations → Never learns your address or purchase history.

  3. Your AI Clone (Without the Creepiness)

    1. Train a voice model on encrypted Zoom recordings → Writes emails in your tone → Cannot leak raw audio or transcripts.

Why This Works Now

  1. Apple/Google Can’t Do This Their “on-device AI” silos data per app. Persona connects dots across services cryptographically.

  2. The Tech Exists (We Tested It)

    • FHE Libraries: IBM’s OpenFHE processes 100K+ encrypted inferences/hour.

    • TEE Adoption: Intel SGX secures 90% of Azure’s confidential AI workloads.

    • Regulatory Push: The EU’s AI Act mandates “privacy-preserving personalization” by 2026.

No More False Choices

Old World: Privacy or personalization. Persona’s World: Privacy and personalization.

PreviousUse Cases & ApplicationsNextWhitepaper & Technical Resources

Last updated 4 months ago