> For the complete documentation index, see [llms.txt](https://build.intract.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://build.intract.io/introduction/faqs.md).

# FAQs

Have some questions about Persona Protocol?

Hopefully, you'll find the answers here! If not then please don't hesitate to reach out to us on [discord](https://discord.gg/TnXjkR5) - there are no stupid questions!

<details>

<summary>What makes Persona different from other “decentralized identity” projects?</summary>

Most protocols focus on *storage* (where data lives). We focus on *computation* (how data is used).

* **Example**: While others let you “store” your medical records, Persona lets hospitals train AI models on **encrypted patient data** without ever decrypting it.
* **Tech Edge**: We combine TEEs (hardware security), FHE (encrypted computation), and ZK proofs (selective disclosure) into one stack—others use just one

</details>

<details>

<summary>How do you protect privacy if AI needs my data?</summary>

Your data stays encrypted during processing. Think of it like this:

* **Old Way**: Give Netflix your watch history → They store it → Recommend shows.
* **Persona Way**: Netflix sends an AI model to your vault → It analyzes **encrypted viewing habits** → Returns recommendations without Netflix ever seeing your data.\
  \&#xNAN;*Powered by Fully Homomorphic Encryption (FHE), tested by JPMorgan for fraud detection.*

</details>

<details>

<summary>Why launch now? Didn’t privacy protocols fail in 2017-2020?</summary>

Three seismic shifts:

1. **AI Crisis**: GPT-5 is hitting accuracy walls due to lack of private data.
2. **Regulatory Teeth**: GDPR fines hit $3B+; eIDAS 2.0 mandates EU digital IDs by 2025.
3. **Tech Readiness**: FHE libraries (IBM) and TEEs (Intel SGX) are now production-grade.\
   \&#xNAN;*Previous protocols were like electric cars without batteries—we have the infrastructure now.*

</details>

<details>

<summary>Can I actually make money with my data?</summary>

Yes, but not by “selling” it. You license **privacy-preserving insights**:

* **Scenario 1**: Earn $5/month letting brands target “dog owners in NYC” via ZK proofs (no address leaks).
* **Scenario 2**: Get paid in crypto for contributing encrypted fitness data to medical studies.\
  \&#xNAN;*No raw data changes hands—only value derived from it.*

</details>

<details>

<summary>How do you handle KYC/AML without exposing my ID?</summary>

* **For Users**: Prove you’re “over 18 + resident of Germany” via ZK proofs from your passport scan. The app learns **only** “yes/no.”
* **For Banks**: Comply with regulations using proofs instead of storing copies of IDs.\
  \&#xNAN;*Piloted with a European neobank to cut KYC costs by 40%.*

</details>

<details>

<summary>What stops hackers from stealing my vault data</summary>

* **TEEs (Trusted Execution Environments)**: Data is processed in hardware-sealed black boxes (used by Microsoft Azure)
* **MPC (Multi-Party Computation)**: Your data is split into encrypted shards; no single breach reveals anything.
* **Zero-Trust Design**: Even Persona’s team can’t access your vault.

</details>

<details>

<summary>How does this help startups compete with Big Tech?</summary>

* **Example**: A travel startup can personalize trips using your **encrypted** Uber/Lyft history. No need to mine data like Google—just query the *privacy-safe insights*
* **Cost**: Integration takes <1 week via our APIs, vs. years to build data pipelines.

</details>

<details>

<summary>What if I want to delete my data?</summary>

* **Atomic Control**: Hit “delete” → Data vanishes from all connected apps.
* **Blockchain Anchors**: A tamper-proof audit trail proves compliance (e.g., GDPR “right to be forgotten”).

</details>

<details>

<summary>How does Persona work with AI agents like ChatGPT</summary>

* **For You**: Let ChatGPT analyze your encrypted calendar to schedule meetings → It never sees event details.
* **For Developers**: Train AI models on **encrypted industry datasets** (e.g., 10,000 encrypted EHRs for drug discovery).

</details>


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