# What is Persona? The Internet’s Missing Layer — Finally Yours
#### **Introducing Persona Protocol** Think of your digital life as a puzzle scattered across 100+ apps. Google knows your searches, Twitter has your hot takes, Steam remembers your gaming wins, and your bank tracks every latte you buy. But *you* don’t own any of it. Instead, these companies hoard your data like dragons guarding gold, using it to trap you in their walled gardens. **Persona Protocol is here to flip the script.** We’re building a *internet's private context network* where **users** decide how your data gets used. Imagine sharing your Twitter cred to instantly prove you’re not a bot on a new social app, or letting an AI assistant analyze your Spotify + Social Interactions to plan your dream vacation—*without handing over raw data*. We enables you to export their raw digital interactions from siloed platforms and convert them into a clear, actionable context. This distilled digital context lets applications deliver tailored, intelligent experiences and better incentives while keeping your underlying data secure. This isn’t just "decentralized identity." It’s **giving your digital self a spine**. This is a **universal layer** where 1. **Users** will be able to a**ggregate data** from apps, chains, and devices into a *personal vault and grant* **license snippets** to apps via privacy-safe "context artifacts" (e.g., *"Proof I’m a Top 10% Call of Duty Player"*). 2. **Developers/AI** get rich insights *without seeing raw data*—like tasting a recipe without knowing the ingredients. ## ## The Why: **The Internet’s Broken Promises** **🔥 *****Big Tech’s Dirty Secret*** Google and Meta became trillion-dollar giants by locking you into their ecosystems. Their "personalized" experiences? Just clever traps to keep you addicted. Want to leave Instagram? Good luck rebuilding your social graph elsewhere. Meanwhile, startups and AI innovators can’t compete. **They’re data-starved.** Without your history, preferences, or trust signals, they’re stuck offering generic, half-baked experiences. **💸 *****Plaid Proved the Hunger*** Plaid’s $15B valuation wasn’t magic—it solved a simple truth: *People want to own and share their data*. But Plaid only handles bank logs. What about your gaming achievements? Your LinkedIn clout? Your ChatGPT conversations? **🤖 *****AI’s Existential Crisis*** AI is about to hit a wall. Today’s chatbots hallucinate because they’re trained on public slop. Tomorrow’s AGI needs *your* private context—your texts, your purchases, your creative drafts—to truly serve you. But unless we fix data ownership, AI will either: 1. Stay dumb (bad for you) 2. Become a privacy nightmare (worse for you) ## ## **The How: Your Data, Your Rules** We’re not building another data protocol. <>. Here’s how we build that: * **Platforms:** We integrate with a wide range of web2 and web3 platforms—think Google, Twitter, Discord, Ethereum, and more. Wherever your data lives, we connect with it. * **Data Artifacts:** These are the individual pieces of data generated by each platform. A tweet, a like, or a bookmarked article—each is a data artifact that tells part of your story. * **Context Artifacts:** Rather than sharing every raw detail, we compute inferences over your data artifacts to create *context artifacts*. These are the meaningful signals that describe your patterns of behavior without exposing the underlying specifics. Any developer can create new context artifacts, and they are computed within a secure enclave cluster to ensure your privacy. * **Context Models:** These are the algorithms that take your data or existing context artifacts and transform them into new, enriched outputs. The result might be a credential, vector embeddings, a knowledge graph, a social graph, or even proofs of various attributes. It’s a flexible framework that enables deeper, personalized insights. * **User Repository:** All your data and context artifacts are stored in a user-controlled repository. This isn’t just a static storage space—it supports multiple formats. For example, you can generate and retrieve vector embeddings (often called RAGs) right from your repository, ensuring that you always have access to your personalized digital context. * **Users:** At the heart of Persona are you—the user. You decide what goes into your repository and what gets shared. Your digital context is your asset, managed on your terms. **Behind the scenes:** * 🔒 *Privacy by Design*: Your raw data never leaves your vault. Apps only get *outputs*—like a chef serving a dish without revealing the recipe. * 🧩 *Lego Bricks for Devs*: Pre-built modules for social graphs, financial trust scores, etc. ## **Why Now?** 1. **AI Needs You** 1. GPT-5 won’t book your flights unless it knows your budget, loyalty points, and fear of turbulence. But you’ll never feed it bank statements unless there’s a *trust layer*. 2. Modern AI and applications need high-quality, contextual signals to deliver experiences that truly resonate. By providing a secure layer of distilled insights, Persona bridges the gap between raw data and smart, tailored services. 2. **Regulators Are Done Waiting** 1. GDPR fines hit $3B last year. eIDAS 2.0 is coming. Apps need privacy tools that don’t kill UX—yesterday. 3. **You’re Tired of Being a Product** 1. A 2024 study found 78% of Gen Z uses ad blockers. We’re all done being Tech Giant's lab rats. 2. Increasingly, people are tired of starting from zero every time they join a new service. With Persona, your digital context becomes portable, allowing you to take your curated insights from one application to another without sacrificing your privacy. 4. **Advancements in Privacy Tech:** 1. With Trusted Execution Environments (TEE), Multi-Party Computation (MPC), and Fully Homomorphic Encryption (FHE) now available, we can process and share context artifacts securely—something that wasn’t possible until recently. ## **Win-Win: Users & Apps** **🚀 Supercharged Apps** * **For Startups**: Compete with giants using *your* data—not theirs. Imagine a TikTok rival that knows your meme preferences *without* spying on your camera roll. * **For AI**: Train models on *real human context* instead of public junk. Smarter chatbots, hyper-personalized health coaches, finance AIs that actually get you. * **For You**: No more “Sign up and start from zero.” Bring your rep, your achievements, your *digital soul* everywhere. **🔑 Privacy ≠ Obscurity** You’re not hiding—you’re **curating**. Share what matters: * Prove you’re a *legit gamer* without leaking your Steam ID. * Let Netflix recommend shows based on your Letterboxd ratings *without giving them your account*. * Help a climate app calculate your carbon footprint *without handing over Uber receipts*. ## **What’s Possible?** 1. **Healthcare AI That Actually Cares:** 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:** 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):** Train a voice model on *encrypted* Zoom recordings → Writes emails in your tone → *Cannot* leak raw audio or transcripts. ## **The Vision** > *"Your phone knows 100x more about you than your best friend. Shouldn’t you control that power?"* Persona Protocol isn’t just about reclaiming privacy—it’s about **unlocking a trillion dollars of stranded value** in your data. From hyper-personalized AI to fairer airdrops, we’re building the plumbing for an internet where: * Users **profit** from their digital selves * Startups **compete** with giants * AI **serves** you, not shareholders **This isn’t Web3. It’s Web *****Me*****.**
*Think we’re crazy?*\ [See how Proof of Humanity is already fighting bots →](https://chat.deepseek.com/a/chat/s/link)\ [Build your first context model (no code needed) →](https://chat.deepseek.com/a/chat/s/link)
*** ## Other Thoughts #### **Overview** **Persona Protocol** is a user-centric data aggregation and context inference protocol that transforms scattered data into actionable insights—without compromising user privacy. By securely aggregating data from a multitude of web2 and web3 platforms into one user-controlled repository, Persona Protocol empowers developers to build truly personalized applications while giving users complete control over their digital identity. Think of it as: > *"A privacy-preserving bridge between your fragmented digital footprints and applications that need to understand you better."* #### **Core Problem** Today’s digital landscape is fragmented. Your data lives on platforms like Google, Twitter, Discord, Ethereum, and many more. This scattered data makes it hard for applications to fully understand you without asking for excessive permissions or compromising your privacy. Traditional methods often force a trade-off between personalization and control, leaving both developers and users unsatisfied. * Users’ data is siloed across 100+ platforms. * Apps today either demand excessive permissions or operate blindly. * Raw data exposure creates privacy risks. #### **Solution** Persona Protocol bridges that gap. We take the raw pieces of data—what we call **Data Artifacts**—from a variety of platforms and transform them into meaningful **Context Artifacts** using advanced algorithms (our **Context Models**). This process unlocks deeper insights into user behavior, interests, and social interactions while ensuring that the sensitive raw data remains protected. The result? A richer, more nuanced context that applications can use to deliver highly personalized experiences without exposing your personal details. 1. **Aggregate** data from Discord, Gmail, Ethereum, etc. 2. **Compute** insights (e.g., "social reputation scores" or "financial trustworthiness") in secure enclaves. 3. **Share** context, not raw data, via user-approved licenses. #### **Key Concepts**
ConceptDescriptionExample
User RepositoryUser-controlled storage for raw data and computed context artifacts.Stores Twitter posts and a RAG embedding of your social interests.
Data ArtifactsRaw user data from platforms (emails, transactions, posts).Your Ethereum wallet history or Gmail attachments.
Context ArtifactsPrivacy-safe insights derived from data (vectors, graphs, credentials).A "DeFi Risk Score" computed from your wallet activity.
Context ModelsAlgorithms that transform data into context (openly contributed by devs).A model that infers your professional skills from LinkedIn/GitHub.
Secure ComputePrivacy-preserving computation in trusted enclaves.Your Gmail data is analyzed without the network ever seeing raw emails.
#### **How It Works** #### 1. **Ingest** * Connect platforms via OAuth/APIs (Web2) or blockchain indexers (Web3). * Data is normalized into schemas (e.g., "social posts," "financial transactions"). #### 2. **Compute** * Users select context models (e.g., "ZK-Identity Proof" or "NFT Collector Score"). * Models run in hardware-secured enclaves; only outputs (context artifacts) are stored. #### 3. **Serve** * Apps request access via [Universal APIs](https://chat.deepseek.com/a/chat/s/link-to-APIs) with user consent. * Users grant time-bound licenses (e.g., "Share my gaming reputation to this dApp for 30 days").
#### **Why Persona Matters** #### For Users 🔐 **Ownership**: Your data never leaves your encrypted repository.\ 🎛️ **Control**: Granular permissions (e.g., "Share my credit score but hide transactions").\ 💸 **Monetization**: Earn tokens when apps license your context artifacts. #### For Developers 🚀 **Rich Context**: Build apps with social graphs, reputation systems, or personalized feeds.\ 🔧 **No Silos**: Universal APIs work across all integrated platforms.\ 🛡️ **Compliance**: Privacy-by-design eliminates GDPR/CCPA risks. # Use Cases & Applications #### **1. AI Applications** **Problem**: AI’s personalization is limited by its inability to safely access private data.\ **Solution**: Encrypted context sharing via FHE (Fully Homomorphic Encryption) and ZK proofs. * **Healthcare AI** * *Use Case*: A diabetes management app analyzes **encrypted glucose levels** (from Freestyle Libre) and **encrypted meal logs** (MyFitnessPal) to suggest insulin doses. * *Delta*: Patients get personalized care; hospitals never see raw data (HIPAA-compliant). * **Financial Advisor AI** * *Use Case*: An AI recommends tax-saving strategies by processing **encrypted bank transactions** and **Crypto.com portfolio data**. * *Delta*: Tailored advice without exposing balances or trade history. * **Travel Assistant** * *Use Case*: An AI plans itineraries using **encrypted Uber ride history** and **Spotify playlists** to suggest destinations aligned with your habits. * *Delta*: Hyper-personalized trips without leaking location data. *** #### **2. Gaming & Consumer Apps** **Problem**: Fragmented identities and fraud undermine trust.\ **Solution**: Portable, privacy-preserving credentials via ZK proofs. * **Skill-Based Matchmaking** * *Use Case*: Prove you’re a "Top 10% Valorant Player" using encrypted match history to skip beginner tiers in new games. * *Delta*: Fair competition; no Steam ID or playtime exposure. * **Secure Asset Trading** * *Use Case*: Sell in-game NFTs using **TEE-secured ownership proofs**—buyers verify authenticity without accessing your wallet. * *Delta*: Fraud-resistant markets; users retain asset control. * **Cross-Game Achievements** * *Use Case*: Unlock exclusive content in *Fortnite* by proving *Apex Legends* wins via ZK proofs. * *Delta*: Unified gaming identity without platform lock-in. *** #### **3. Marketplaces & E-Commerce** **Problem**: Trust gaps and inefficient targeting.\ **Solution**: Privacy-first reputation and intent signals. * **Fraud-Resistant P2P Marketplaces** * *Use Case*: Sell a laptop on a decentralized eBay by proving "100% Seller Rating" via encrypted transaction history. * *Delta*: Buyers trust credentials; sellers hide past buyer details. * **Privacy-First Ads** * *Use Case*: A pet brand targets users who prove "Dog Owner" status via ZK proofs (vet records + Chewy purchases). * *Delta*: Precision targeting without exposing addresses or breeds. * **Instant KYC for Gig Platforms** * *Use Case*: Freelancers reuse **encrypted ID/payroll data** from Upwork to join Fiverr in 1 click. * *Delta*: 80% faster onboarding; no repeated document uploads. *** #### **4. Healthcare & Public Services** **Problem**: Data silos hinder research and aid distribution.\ **Solution**: Secure aggregation of sensitive data. * **Medical Research Acceleration** * *Use Case*: 10,000 patients share **encrypted EHRs** (electronic health records) for cancer drug trials. * *Delta*: Researchers spot trends; no individual data exposed. * **Disaster Relief Targeting** * *Use Case*: Governments verify flood victims’ residency via **ZK proofs of utility bills** without collecting names. * *Delta*: Aid reaches real victims; reduces fraud by 60%. *** #### **5. Finance & Loyalty Programs** **Problem**: Costly compliance and generic rewards.\ **Solution**: Reusable credentials and zero-knowledge verification. * **Credit Scoring Without SSNs** * *Use Case*: Prove creditworthiness using **encrypted cash flow patterns** (bank APIs) instead of FICO scores. * *Delta*: Unbanked users access loans; lenders reduce default risk. * **Dynamic Loyalty Rewards** * *Use Case*: Starbucks offers free coffee after you prove (via ZK) 10 encrypted Uber rides to their stores. * *Delta*: Personalized rewards; Uber never shares ride details. *** #### **6. Social & Identity Verification** **Problem**: Bots and fake profiles erode trust.\ **Solution**: Proof of Humanity (PoH) with privacy. * **Bot-Free Social Networks** * *Use Case*: New platforms like "Threads 2.0" require **ZK proofs of human activity** (e.g., verified Gmail usage) to post. * *Delta*: 90% fewer spam accounts; real conversations thrive. * **Dating App Trust** * *Use Case*: Prove you’re "Single + Employed" via encrypted LinkedIn/Tinder cross-checks without exposing employer or photos. * *Delta*: Authentic connections; no catfishing. *** #### **7. Cross-Industry Portability** **Problem**: Data silos create friction.\ **Solution**: Unified, user-owned data layer. * **One-Click Car Rentals** * *Use Case*: Rent a car using **reusable KYC** (verified via Persona) + **encrypted driving history** from Uber. * *Delta*: 60-second signup; no manual forms. * **Global Talent Marketplaces** * *Use Case*: Developers prove "Top 1% GitHub Contributor" status to join freelance platforms like Toptal. * *Delta*: Instant credibility; no third-party audits. # 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.
# Whitepaper & Technical Resources {% hint style="info" %} Coming soon {% endhint %} # 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!
What makes Persona different from other “decentralized identity” projects? 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
How do you protect privacy if AI needs my data? 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.\ *Powered by Fully Homomorphic Encryption (FHE), tested by JPMorgan for fraud detection.*
Why launch now? Didn’t privacy protocols fail in 2017-2020? 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.\ *Previous protocols were like electric cars without batteries—we have the infrastructure now.*
Can I actually make money with my data? 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.\ *No raw data changes hands—only value derived from it.*
How do you handle KYC/AML without exposing my ID? * **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.\ *Piloted with a European neobank to cut KYC costs by 40%.*
What stops hackers from stealing my vault data * **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.
How does this help startups compete with Big Tech? * **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.
What if I want to delete my data? * **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”).
How does Persona work with AI agents like ChatGPT * **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).
# System Architecture ### Protocol Overview Intract Protocol is a secure protocol which enables users to store all their private data securely using same standards. The data is encrypted and controlled only by the user. Users have complete control, being able to share selected data segments with trusted authorities—such as AI agents—without exposing the raw underlying information. This ensures that any computations are performed securely, and only the processed results are shared. ### Architecture Overview

The four hoursemen of Intract Protocol

The architecture comprises of 4 layers (or 4 horsemen). These 4 layers form the core of the protocol that allows us to achieve all of the system objectives. Let's explore each of these layers. Each of these layers handle a specific aspect of data management. (We will dive deeper into each one later) 1. #### Ingestion Layer: Data Ingestion Engine (DIE) * **Role:** Securely handles acquiring and importing of user data from various sources (e.g., social media, email) after obtaining user permission. * **Non-Technical Analogy:** Think of this layer as the "data pickup" phase—collecting your information securely. 2. #### Access Layer: Secure Access Management (SAM) * **Role:** Manages permissions and controls access, ensuring only authorised entities can view or use specific data segments. * **Non-Technical Analogy:** Similar to a security guard who ensures that only the right people have access to your private vault. 3. #### Storage Layer: **ENCRYPTED STORAGE SERVICE (ESS)** * **Role:** Enables the user to store their data in an encrypted format, ensuring that even if intercepted, the data remains secure. * **Non-Technical Analogy:** Imagine a high-security vault where your valuables are kept under advanced locks. 4. #### Compute Layer: **TRUSTED EXECUTION CLUSTER (TEC)** * **Role:** Executes secure computations on the encrypted data using a decentralised TEE network, exposing only the processed results to third parties. * **Non-Technical Analogy:** Like hiring a trusted expert who can work on your secret recipe without ever seeing the full details—only the final dish is served. ### A (very) simplified data flow The following steps outline the journey of user data through our system: 1. **User Authorization:** * The process begins with the user granting permission to ingest data from various platforms. 2. **Data Ingestion:** * The Ingestion Layer manages collection of this data and prepares it for secure storage. 3. **Secure Storage:** * Collected data is encrypted and stored in the Storage Layer. 4. **Access Management:** * When a third party or an application requests data, the Access Layer verifies the permissions and ensures that only authorized data or computed results are shared. 5. **Secure Computation:** * The Compute Layer performs decentralized, secure processing on the data, providing only the results to the requester without exposing raw data. ### Key Architectural Features * **Layered Security:**\ Each layer incorporates specific security measures, ensuring robust protection at every stage. * **Decentralized Computation:**\ Utilizing a decentralized Compute Layer reinforces trust and minimizes the risk of data manipulation or leakage. * **User-Centric Design:**\ The architecture is designed with the user in mind, prioritizing privacy, control, and seamless data portability. * **Scalability & Flexibility:**\ Our modular design facilitates the addition of new data sources and adapts to evolving security challenges. # Protocol Components The protocol has 4 components or 4 pillars of the Intract Protocol 1. Data Ingestion Engine (DIE) 2. Encrypted Storage Service (ESS) 3. Trusted Execution Cluster (TEC) 4. Secure Access Management (SAM) Each of these component/layer is developed to be independent of each other so that each of them could be upgraded and enhanced independently based on the requirements of use cases. Network participants can choose which layer they want to support. Also decoupling these things means better security for the user as the power that resides in the protocol is also distributed across components and they each ensure each other's security. Read more about each component in coming sections. # Data Ingestion Engine (DIE) / Ingestion Layer ### Overview The Ingestion Layer is the first point of interaction for users looking to add their data to our system. Whether it’s tweets from Twitter, Discord messages, emails, bank statements, or any other type of data, this layer is responsible for securely fetching, validating, and formatting the data. The system supports multiple data sources and methods of ingestion to ensure flexibility and comprehensiveness. Key functions of the Ingestion Layer include: * **Data Collection:** Aggregating data from various external services and user uploads. * **Data Structuring:** Organizing data in a consistent, accessible format. * **Data Verification:** Validating the authenticity and integrity of the data. * **Up-to-date Synchronization:** Ensuring that data remains current with real-time updates or periodic checks. ### Components #### Ingestion Modules This is the core functionality of the ingestion layer. These are the pieces of codes to ingest and verify the authenticity of any given data - e.g. we need some code to ingest the twitter tweets. Now this piece of ingestion layer needs to know the twitter api response structure etc. Other kind of ingestion modules might be based on new technologies like zkTLS etc. Currently we support the following Ingestion Methods: 1. API Based Ingestion 2. zkTLS Based Ingestion 3. OAuth Based Ingestion 4. Raw Data Upload More methods to be added as required #### Scheduler The role of ingestion scheduler will be to: 1. Update refresh tokens if necessary (in case of OAuth) 2. Schedule fetching jobs for when for recurring data sourcing. #### Bridges The role of bridges is to transform data from one format to other. For example: if the given response is in csv and the application required is in json, so we need to run a bridge on the data to convert it in required format. # Trusted Execution Cluster (TEC) / Compute Layer ### Overview The Compute Layer is responsible for processing encrypted data securely using Trusted Execution (TE) nodes. These nodes run specialized compute programs on data without exposing the raw inputs. The Compute Layer seamlessly integrates with the rest of the system, ensuring that all computations are performed securely and efficiently. *** ### TEE Nodes Structure The Compute Layer is comprised of multiple TEE nodes that execute computation jobs in isolated and secure environments. Each of these nodes will run a software provide by Intract to ensure adherence to our guidelines and prevent any malicious behaviour. Also when a node joins the network, it is allocated a special NFT which works as an identity card of the network to prove to third parties (e.g. Lit Protocol) that it is part of the Intract Network. This could be redacted at any time in case of malicious behaviour. When a job arrives to the TEE network for compute, all nodes which are up at that time are eligible to run it and it is allocated based on the amount staked as well as the reputation of the node. Everytime a node successfully completes a job, their reputation is increased and fees is allocated to them. However in case of any malicious reports, the reputation could be reduced and the stake could also be slashed. *** ### Compute Job Input Structure For each compute job, the following input components are provided: 1. **Encrypted Data:** * The data to be processed is encrypted with a designated key. 2. **Decryption Method & Parameters:** * **Decryption Method:**\ Specifies the method to decrypt the input data. * **Decryption Parameters:**\ Associated metadata required for decryption, which is itself encrypted using the TEE node's private key. * *Example:* The primary decryption method supported is the **LIT protocol**. For more details on the LIT protocol, please refer to the LIT Protocol Documentation. 3. **Compute Program:** * The actual program or script that needs to be executed on the decrypted data. This could be an ingestion module, a context model, or any other supported compute task. 4. **Result Encryption Key:** * The key that will be used to encrypt the final computation result before it is transmitted or stored. *** ### Supported Decryption Methods The Compute Layer supports multiple decryption methods to ensure flexibility and security. The primary decryption method is: * **LIT Protocol:** * Uses session keys to securely decrypt data. * The decryption parameters necessary for the LIT protocol are provided as part of the job input. * For comprehensive details on the LIT protocol, please refer to the LIT Protocol Documentation. *Note:* Additional decryption methods may be supported in future updates. The protocol’s modular design allows for easy integration of new decryption techniques as needed. *** ### Advanced Compute Methods for AI Agents In addition to running traditional compute programs on decrypted data, our Compute Layer supports advanced AI-driven compute methods that transform raw data into specialized outputs. Depending on the nature of the input data and the specific requirements of the application, the secure compute environment can produce various structured outputs, such as: * **Vector Database (VectorDB) Embeddings:**\ For applications like information retrieval or semantic search, the compute node can convert raw data (e.g., emails, documents) into high-dimensional vector embeddings. These embeddings are then stored in a VectorDB, enabling fast and efficient similarity searches. For instance, if an AI agent queries travel-related information from a set of emails, the system can generate vector embeddings that capture the semantic essence of travel-related content, rather than exposing the entire email data. * **Knowledge Graphs:**\ When the context and relationships within the data are crucial, the compute node can generate a knowledge graph. This structured representation captures entities, relationships, and attributes from the input data, facilitating complex reasoning and insights. For example, a knowledge graph built from emails might reveal connections between contacts, topics, or events related to travel. * **Retrieval-Augmented Generation (RAG):**\ In scenarios where a condensed and query-specific representation is needed, the compute node may generate a smaller, focused Retrieval-Augmented Generation output. This involves summarizing or embedding only the relevant portions of the raw data, thereby optimizing the output for the AI agent's query while maintaining data privacy. *** ### Workflow & Data Flow 1. **Job Submission:** * A compute job is initiated with the full input set (encrypted data, decryption method, metadata, result encryption key, and compute program). 2. **Decryption Process:** * The TE node retrieves the encrypted data and, using the specified decryption method (e.g., LIT protocol), decrypts the data with the provided parameters. 3. **Execution of Compute Program:** * Once decrypted, the compute program is executed on the data. The program may process, transform, or analyze the data as required. 4. **Result Encryption:** * After processing, the resulting data is encrypted using the provided result encryption key. 5. **Result Delivery:** * The encrypted result is then securely transmitted back to the requesting entity or stored as per system requirements. # Secure Access Management (SAM) The Access Layer is the core component of our protocol, governing who can access and decode user data. It provides a robust and flexible framework for managing permissions, ensuring that data is only accessible according to user-defined rules. This layer plays a critical role in maintaining privacy and enabling secure data computations. ### Access Control Mechanisms The Access Layer supports two primary forms of user-controlled permissions: ### Initial Data Storage Permissions * **Description:**\ When users add data to the system, they decide the privacy level of that data. * **Options:** * **Private:**\ Data remains encrypted and only accessible by the user unless explicit permission is given. * **Publicly Queryable:**\ Data can be queried by certain trusted applications or services, while still maintaining a controlled access model. ### Third-Party Compute Permissions * **Description:**\ Users can grant third parties access to run computations on their data. * **Control Parameters:** * **Scope of Access:**\ Users define which segments of data a third party can access. * **Access Frequency:**\ Users set limits on how often a third party may access or query the data. * **Data Format:**\ Permissions can specify whether a third party receives only the computed result or the raw data (if needed). * **Dynamic Controls:**\ These permissions can be updated or revoked at any time to adapt to changing privacy or operational needs. *** ### Distributed Ledger for OAuth Records The technological backbone of the Access Layer is a distributed ledger that records every OAuth call and permission grant. This ledger ensures a tamper-proof, auditable record of access permissions. * **Unique OAuth ID:**\ Each access grant is recorded with a unique identifier. * **Permission Set:**\ Details about the specific permissions (scope, frequency, data format) are stored. * **Decryption Parameters:**\ When access is granted, the relevant decryption parameters are encrypted using the compute’s public key. * **Validation Process:**\ When a third party presents an OAuth token, the protocol verifies it against the distributed ledger. If valid, the corresponding compute job is scheduled, and the necessary decryption parameters are provided to the compute module. *** ### Data Flow & OAuth Record Lifecycle 1. **User Permission Setup:** * The user specifies how data should be stored and who can access it. * A unique OAuth record is created and recorded on the distributed ledger. 2. **Access Request:** * When a third party or compute job requests access, it presents an OAuth token. * The protocol checks the distributed ledger for a matching record. 3. **Validation & Scheduling:** * If the OAuth token is valid, the compute job is scheduled. * The decryption parameters (encrypted with the compute's public key) are released to enable secure computation. 4. **Post-Processing:** * Once the computation is complete, the output is securely shared with the third party as defined by the user’s permissions. # Encrypted Storage Service (ESS) / Storage Layer ### Overview The Storage Layer is designed to manage pointers to encrypted raw data rather than holding the data in a directly accessible format. It acts as the intermediary that: * Accepts encrypted data along with storage location metadata. * Stores the data using the appropriate storage method. * Returns a unique object identifier for each stored data object. * Maintains a mapping between object IDs and their corresponding storage locations. * Verifies data integrity by calculating and checking data checksums. All data handled by this layer is encrypted and remains inaccessible to any internal or external parties without proper authorization. *** ### Core Functions #### Pointer Management & Object ID Generation * **Data Ingestion:**\ When encrypted data is provided, it comes with a designated storage location and relevant metadata (e.g., bucket details for S3). The Storage Layer validates that it can store the data at the specified location. * **Object ID Generation:**\ Once validated, the layer stores the pointer information and returns a unique object ID to the application. This ID is used for future reference and retrieval. #### Data Integrity Verification * **Checksum Calculation:**\ A checksum is computed when data is stored to ensure that the data remains unaltered. * **Verification on Retrieval:**\ When data is queried via its object ID, the Storage Layer verifies the checksum to confirm that the retrieved data is exactly as originally stored. #### Data Retrieval * **Pointer Lookup:**\ Upon receiving an object ID, the Storage Layer identifies the appropriate storage method and location. * **Fetching & Verification:**\ The data is fetched from its storage location and the checksum is validated before returning the encrypted data to the requester. *** ### Supported Storage Methods The Storage Layer supports multiple storage solutions to provide flexibility and redundancy: * **S3:**\ Data is stored in Amazon S3 buckets. Metadata includes bucket names and region details. * **MongoDB:**\ Data pointers and associated metadata can be stored in a MongoDB collection. * **IPFS:**\ Data stored in a decentralized manner using the InterPlanetary File System. * **Local Storage:**\ For on-premise or development purposes, data can be stored locally, with metadata specifying the local path or directory. Each storage method is integrated through modular functions that handle data input, pointer mapping, and integrity verification. # Security Implementations Our system is designed with a layered security approach to protect sensitive user data and ensure that only authorized parties can access or process this information. Here’s how security is maintained throughout the workflow: ### Data Encryption and Key Management * **Asymmetric Encryption:**\ Each stakeholder (User, Dapp, TEC, etc.) uses a unique private/public key pair. * **User Keys:** The user's private key is generated and stored only on their device, while the public key is shared with the network. This ensures that any data meant for the user can only be decrypted on their device * **Dapp Keys:** The Dapp's private and public keys are used for signing requests and encrypting final computed results, ensuring that only the intended Dapp can decrypt the data. * **TEC Keys:** TEC employs a key pair (with additional mechanisms from Lit Protocol) to encrypt and decrypt data securely during computation. This means even when data is in transit or being processed, it remains inaccessible to unauthorized entities. * **Token Encryption:**\ OAuth tokens from Twitter are encrypted immediately upon retrieval using TEC’s public key, ensuring that tokens are never exposed in plaintext. ### Secure Multiparty Computation (MPC) * **Lit Protocol Integration:**\ The TEC leverages secure multiparty computation (MPC) through Lit Protocol to validate decryption requests. This ensures that no single party has full control over the decryption process. * **Validation of Requests:** Decryption keys and parameters are only released if a valid, authorized request is made, preventing unauthorized data access. * **Distributed Trust:** The MPC approach means that sensitive operations are split across multiple nodes, reducing the risk of a single point of compromise. ### Data Handling and Storage * **Minimization of Data Exposure:** * **No Raw Data Sharing:** The Dapp receives only the computed result from the secure computation; raw user data (such as tweets or Twitter IDs) is never shared directly with the Dapp. * **Ephemeral Tokens:** Sensitive tokens are encrypted, stored securely, and accessed only for the duration of the computation, reducing the risk of misuse. * **Secure Storage with ESS:**\ Encrypted data is stored on a third-party service (e.g., AWS) but is only accessible through secure pointers maintained by ESS. * **Data at Rest:** All stored data is encrypted, ensuring that even if storage is compromised, the data remains inaccessible without the proper decryption keys. * **Pointer and Parameter Storage:** ESS securely stores pointers, ensuring that even when data is retrieved, only authorized processes can decrypt it. ### Access Control and Authorization * **Permission-Based Data Access:** * **User Authorization:** Users must explicitly grant permissions for their data to be accessed and processed. This is achieved through a secure OAuth flow, where the user’s consent is mandatory. * **Scoped Data Requests:** The system is designed so that the Dapp can only request the final computed results rather than direct access to raw data, ensuring that user privacy is maintained. * **Verification of Real Users:** * **Key Generation on First Signup:** Every new user generates a private/public key pair upon joining the Intract Protocol, ensuring that each entity in the system is uniquely identified. * **Digital Signatures:** All transactions and data exchanges are signed using the respective stakeholder’s private key, which verifies the authenticity of the request and ensures that only real, authorized parties can initiate secure data processing. ### End-to-End Data Integrity * **Data Integrity Checks:**\ Throughout the data processing workflow, integrity checks (e.g., cryptographic hashes) are employed to ensure that data has not been tampered with during transit or storage. * **Audit Trails:**\ Every key transaction—from OAuth token generation to final result delivery—is logged. These audit trails help in identifying and mitigating potential security incidents and ensuring compliance with data protection standards. *** This multi-layered security design guarantees that sensitive user data remains secure at every stage of the workflow, and that only verified and authorized entities can access or process the data. # A detailed example on how it works This document outlines the end-to-end process—from user interaction to secure computation and data storage—detailing all participants, attributes, and the workflow. It demonstrates how the Dapp leverages the Intract Protocol to securely compute Twitter-based rewards without exposing sensitive user data. *** ### The Problem Statement #### Situation **Context**\ A user logs into a decentralized application (Dapp) using their wallet. The Dapp runs a points system to reward users for posts that generate high engagement on Twitter. **Challenge**\ The user wants to prove their Twitter engagement (for rewards) without revealing their Twitter ID or exposing the actual posts. Assumptions\ It is assumed that the user is signing up on the Intract Protocol for the first time, during which their key pair is generated and permissions are set. *** #### Solution **Overview:**\ The Dapp leverages the Intract Protocol, which integrates components like ITCC, IAMS, IIM, and ISS, to execute a permissionless, secure computation. This ensures that sensitive data (Twitter ID and posts) is never directly exposed to the Dapp. **Key Features:** * **Data Privacy:** Users’ Twitter data remains encrypted and private. * **Decentralized Security:** Utilizes cryptographic key pairs and secure multiparty computation (MPC) via Lit Protocol. * **Seamless Integration:** Dapp integrates via an SDK, simplifying the adoption of the Intract Protocol. *** ### Detailed Workflow #### Key Participants * **Dapp (D):**\ The decentralized application that registers on the Intract Protocol and requires the computed results. * **User (U):**\ The end user who logs in with their wallet and authorizes data processing without disclosing sensitive details. * **Intract TEE Compute Cluster - (ITCC) aka TRUSTED EXECUTION CLUSTER (TEC)**\ Executes the compute job, decrypts tokens using its private key, fetches data, runs the context model, and encrypts results. * **Intract Access Management Service (IAMS) aka SECURE ACCESS MANAGER (SAM)**\ Manages user authorization and OAuth integration with Twitter. * **Intract Ingestion Module (IIM) aka DATA INGESTION ENGINE (DIE)**\ Schedules and initiates the ingestion jobs based on user permissions and selected recurrence. * **Intract Storage Service (ISS) aka ENCRYPTED STORAGE SERVICE:**\ Stores encrypted data securely for future reference. #### Key Parameters * **Compute Algorithm/Context Model (CM):**\ The algorithm defined by the Dapp to process tweets and compute a user’s reward score. * **User Private/Public Key Pair:**\ Generated upon first signup; the private key remains on the user’s machine while the public key is shared across the network. * **Dapp Private/Public Key Pair:**\ Used for secure communication and data encryption/decryption with the Dapp. * **TEC Private/Public Key Pair:**\ Implemented using Lit Protocol to enforce MPC and validate decryption requests. #### Final Workflow 1. **Dapp Registration & Setup:** * The Dapp registers on the Intract Protocol, obtaining its private and public keys. * A new context model (CM) is created and verified. * The Dapp integrates the protocol using the provided SDK. 2. **User Login & Initiation:** * The user logs into the Dapp with their EVM wallet address. * The Dapp presents a button labeled **"Calculate Tweet Bonus using Intract Protocol."** 3. **Redirection & Key Generation:** * On clicking the button, the user is redirected to the Intract Protocol portal (e.g., `keys.intract.io`). * A public/private key pair is generated for the user if not already created (private key remains on the user’s machine). 4. **Permission Request:** * The user authorizes Intract Protocol to: * Fetch, encrypt, and store all tweets. * Allow the Dapp to securely execute the compute model on the tweets, receiving only the computed result (no raw data or Twitter ID). * The user is prompted to connect their Twitter account via OAuth. 5. **OAuth & Data Encryption:** * The Twitter OAuth service provides a token to IAMS. * IAMS encrypts the token with ITCC's public key and stores it along with details (user public key, platform, token grant date, token expiry date, etc.) in the OAuth table. 6. **Job Scheduling & Data Ingestion:** * Based on the user-selected recurrence, IAMS instructs IIM to schedule an ingestion job. * IIM creates a compute job with parameters including OAuth details, user public key, app ID, and compute model. 7. **Computation & Secure Processing:** * ITCC receives the job and: * Uses its private key to decode the OAuth token. * Fetches user data (tweets) via the IIM-provided module. * Runs the context model (CM) on the data to compute the final result (R). * Encrypts the processed data using the ITCC public key along with additional parameters provided by Lit Protocol. * The encrypted decryption parameters are then re-encrypted with the user’s public key. 8. **Storage & Result Delivery:** * The processed and encrypted data is stored by ISS in a secure third-party service (e.g., AWS). * A pointer to this data is maintained by ISS. * The final result (R) is encrypted using the Dapp’s public key and sent to the Dapp. * ISS also stores a reference (including OAuth table primary key and decryption parameters) for future use. *** > 1. User data (Twitter credentials, raw tweets) is never stored in plaintext. > 2. Only the computed result is shared with the Dapp, ensuring privacy. *** ### Advantages of This Flow * **Data Privacy & Security:**\ Users can leverage their social media engagement without compromising their personal data. * **Decentralized Verification:**\ The use of cryptographic keys and secure computation ensures that only authorized computations occur. * **Ease of Integration:**\ Dapps can integrate with the Intract Protocol using a straightforward SDK, reducing development overhead. * **Scalability:**\ The modular design (with separate components for ingestion, computation, and storage) allows for easy scaling as user demand increases. *** ### Considerations & Future Enhancements **Optimizations:** * Automate re-keying or periodic reauthorization for returning users. * Optimize the context model for performance as data volume grows. **Additional Work:** * Explore enhancements in error handling and recovery processes. * Integrate additional social media platforms to broaden the scope of rewards. *** {% @mermaid/diagram %} # Building Apps {% hint style="info" %} Coming Soon {% endhint %} # Welcome At Persona Protocol, our mission is simple - to be the safest, slickest data layer in the universe! Our system allows you to access data from applications, blockchains, and devices securely and efficiently. Developers and AI agents can gain valuable insights without directly viewing the original data. It’s data magic - sweet, simple, and no mess! This guide is your key to unlocking our tools and boosting your tech capability. We’re here to guide you in crafting standout solutions, no extras needed. We’ve split this guide into six short parts for simplicity. Follow them step-by-step, and you’ll soon be using our system to create impressive applications.
Partner ShowcasesPartner Showcase.jpgPartner Showcase
ApplicationsApplications.jpgApplications
Ideas you can stealIdeas for you.jpgIdeas you can steal
Grant ProgramGrants.jpgGrant Program
Infrastructure PartnersInfra Partners.jpgInfrastructure Partners
Contact UsContact Us.jpgGet Involved
Ready to jump in? Let’s get going! # Partner Showcase #### AI Agent Frameworks Our protocol enables agents built on following frameworks to easily connect user private context in form of embeddings or knowledge graphs to create more powerful personalised experiences for users.
Eliza (Coming Soon)_-Lc1h51_400x400.pngEliza
AIXBT (Coming Soon)UPaVddbm_400x400.jpgAIXBT
Virtuals (Coming Soon)kh5ynoMH_400x400.jpgVirtuals
Eternal AI (Coming Soon)eUNd5B4d_400x400.jpgEternal AI
# Eliza {% hint style="info" %} Coming Soon {% endhint %} # AIXBT {% hint style="info" %} Coming Soon {% endhint %} # Eternal AI (Similar to Virtuals) {% hint style="info" %} Coming Soon {% endhint %} # Virtuals {% hint style="info" %} Coming Soon {% endhint %} # Applications By now, you’ve likely noticed the direction we are heading. We’re here to make things personal and seamless for you, like a trusty guide in the digital world. To add some context, let’s look at a few apps we’ve helped build. These applications use our framework to deliver personalized experiences that adapt to you over time. They’re out there working smoothly, ensuring every interaction feels tailored and meaningful. With us in the mix, these tools keep getting better at understanding what you need.
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Intract QuestsTargeted User Acquisition and IncentivesQuests.jpg
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# Targeted Intract Quests Precision User Acquisition Powered by Persona Protocol
Quests is a marketplace app where projects create tasks for you to complete and offer rewards in return. We keep your privacy front and center with Persona Protocol. Quests has grown to 6 million users across 200 countries, generated $1 billion in activity, and partnered with names like Linea, MetaMask, Berachain, Starknet, and over 2,000 others. Pretty impressive, right? ### How It Works with Persona Protocol #### 1. Targeting Users Without Snooping We gather some info from questers - like wallet balances, transactions, or social activity - and store it in your **Persona Repository**. It’s a secure spot questers fully control. Projects use our **Context Models** to find people like them without accessing their private details. Here are some examples: * **TVL Optimization**: Spots users with funds in underused pools. * **OG Detection**: Identifies long-time or active community members. * **Airdrop Propensity**: Finds wallets that hold onto airdropped tokens. * **Developer Reputation**: Confirms coding contributions via GitHub. These models run in our **Secure Enclaves** - a safe zone where your raw data stays untouched and private. #### 2. Verifying Your Tasks Securely When any quester finish a quest - like “Add liquidity to Pool X” - we create a ZK-proof from their **Persona Repository**. It’s a way to confirm they have completed the task without revealing sensitive info, like their wallet details. Projects get a simple “done” signal and trust the process - no extra digging needed. #### 3. The Marketplace: Connecting You and Projects Projects post tasks with specific targeting rules, and questers pick the ones that interest them. We also have a **Context Model Marketplace** where developers share targeting ideas - like a “DeFi Power User” model - for others to use. It’s a straightforward way to match projects with the right people. ### What You Get Out of It * **For Projects**: They cut user-finding costs by 60% with precise targeting and avoid fake accounts entirely. * **For Questers**: They earn rewards without sharing personal financial or social details. They decide what data to reveal. * **For Us**: We process over 500,000 verifications daily, showing our system can handle serious scale. ### Why It Matters Quests shows how Persona Protocol balance accuracy and privacy: * **Smart Targeting**: We use tailored models instead of scooping up tons of data. * **Reusable Reputation**: Your status - like being an “OG” - works across blockchains, saving time. * **Efficiency**: Projects like Linea onboarded users 90% faster using our pre-built info. In short, Quests makes it easy for projects to find the right people and for users to earn rewards through Persona Protocol - all while keeping things private and secure. # Proof of Humanity & \[X] Welcome to the future of digital identity verification.
Intract’s Proof of Humanity (PoH) is a tool built on Persona Protocol to solve a big problem in web3: proving someone is a real person without invading their privacy. It uses Persona’s tech to set a new standard for safe, fake-proof identities in decentralized systems. ### How It Works with Persona Protocol #### 1. **Aggregating Cross-Platform Identities** PoH uses Persona’s **Data Artifacts** to securely unify a user’s identities (Twitter, Discord, Ethereum wallets, etc.) into a single, private profile. Raw data remains encrypted in the user’s **Persona Repository**, while PoH accesses only permissioned metadata (e.g., activity patterns, tenure). #### 2. **Dynamic Humanity Scoring** PoH developed a proprietary **context model** that analyzes aggregated **Data Artifacts** to compute a “Humanity Score” (0-100). This model runs within Persona’s **Secure Enclave Cluster**, ensuring raw data is never exposed. The score updates dynamically as new **Data Artifacts** are added (e.g., a user’s new Discord activity raises their score). #### 3. Minting Verifiable Credentials Users can mint their Humanity Score as a **soulbound NFT**. This NFT acts as a publicly queryable **Context Artifact.** Projects verify scores via a ZK-proof, ensuring privacy. \*\*\*\* Users retain full control, deciding who can view their score and having the ability to update or hide it at any time. ### Why It Matters * **For Developers**: A plug-and-play identity layer. Integrate PoH’s pre-trained model via a 10-line API call or customize it using Persona’s tools. * **For Users**: Own and selectively share proof of humanity—no KYC, no data leaks. * **For the Protocol**: PoH’s model is now used by 200+ projects to filter 4M+ monthly sybil attempts, showcasing Persona’s scalability. # Ball-E, Personal AI Agent Your truly personalized DeFAI {% embed url="" %} Say hello to **Ball-E AI Agent**, a clever little sidekick cooked up by some brainy third-party devs using *our* Persona Protocol magic. It gives personalized DeFi advice by looking at data users choose to share. Ball-E turns your blockchain activity and social habits into useful tips to help you get more out of DeFi communities and money-making opportunities - all while keeping your info private. ### How It Works with Persona Protocol #### 1. Contextualized On-Chain Profiling Balle retrieves approved data from users' **Persona Repositories**, including: * **Transaction Context:** Categorized on-chain activities like liquidity provision and airdrop participation. * **Community Engagement:** Discord roles, Twitter follows, and governance voting history. Also, instead of just showing raw transactions, Ball-E analyzes enhanced data points like “DeFi Risk Appetite” or “NFT Collector Score,” generated using Persona’s privacy-focused models. #### 2. **Knowledge Graph Construction** Ball-E uses Persona’s **Context Models** to create a real-time **Knowledge Graph** that tracks: * **User-Project Connections**: Which dApps a user interacts with, how often, and the transaction value. * **Community Affiliations**: DAO memberships, social media activity, and event participation. This graph updates automatically whenever new **Data Artifacts** *(like a Snapshot vote)* is added to the user’s profile. #### 3. **Privacy-First Personalization** Recommendations are created within Persona’s secure system, keeping raw data fully private. For Example “Join DAO X’s liquidity mining program based on your Curve activity”. Also, Users can approve AI actions with detailed permissions. For Example: “Allow Balle to suggest protocols that fit my risk profile”. ### What You Get Out of It * **For Users:** Users can benefit from a 40% average increase in community rewards by leveraging tailored participation strategies while enjoying full transparency, as they can audit AI logic through open-source context models. * **For Projects:** Ball-E driven users show 3x higher retention in partnered DAOs/ecosystems. * **For the Protocol:** Persona showcases its adaptability for third-party AI/ML developers by offering over 15 models in the Context Model Marketplace, enabling seamless integration and enhanced capabilities. ### Why It Matters Ball-E shows how Persona Protocol enables ethical AI innovation: * **Data Sovereignty**: Users only share insights, not personal data. Ball-E cannot access wallets or social accounts directly. * **Interoperable Intelligence**: AI models created for Ball-E can be used in other apps, like a lending platform using "DeFi Engagement Scores.” * **Trusted by Many:** More than 50,000 users rely on Balle for strategy optimization, proving Persona’s privacy-first approach works. # Ideas you can steal Steal these ideas, remix them, and ship something extra ordinary. We’ve got some spicy ideas for you to snatch, tweak, and turn into pure gold. #### Let’s roll! ### 1. A Safer Plaid for Web3 ***Problem:*** Old-school finance apps (like Plaid) make you share private login details, which is risky. ***Fix:*** Make a Web3 version using Persona Protocol. Let users control their own data - like bank accounts, crypto wallets, and taxes - in a secure Persona Repository. Apps only get simple summaries (like “can they pay?” or “how much do they spend?”) instead of everything. Use privacy tech (ZK-proofs) to prove stuff like income or wealth without showing the details. ### 2. Smart AI Helpers That Really Know You ***Problem:*** AI like ChatGPT doesn’t know much about you unless you tell it every time. ***Fix:*** Build AI agents that grab info from Persona - like your travel plans from Gmail or your crypto habits from your wallet. They’d act like a personal assistant, booking trips, picking investments, or finding cool NFTs, all based on what you like, not creepy tracking. ### 3. Hiring Web3 Devs with Proof They’re Good ***Problem:*** It’s hard to hire Web3 talent - resumes can lie, and GitHub doesn’t show the full picture. ***Fix:*** Create a hiring site using Persona to make verified “reputation proofs”: * *Code Score:* Combines GitHub work, Gitcoin projects, and protocol contributions. * *DAO Score:* Tracks votes, posts, and wins in Web3 communities. * *Skill Badges:* Privacy-proofed certificates for skills like Solidity coding. ### 4. Trust Boost for India’s ONDC ***Problem:*** India’s Open Network for Digital Commerce (ONDC) needs trust to beat Amazon. Sellers’ reputations don’t move between platforms. ***Fix:*** Use Persona to pull together seller info (orders, returns, ratings) into one reputation score. Build a system that: * Gives a “Seller Trust Score” based on speed, quality, and happy customers. * Lets buyers pick sellers with verified perks (like “real handmade goods” proven by supply chain data). #### **Grab These, Build These** We’ve got the tech. The world’s drooling for it. So, what’s holding you back from being the next Web3 wizard? Pick an idea, crack open a repo, and ping us when you ship - because we *know* you’re about to drop something Persona-lly spectacular. # Grant Program We respect companies who respect user privacy Build the next generation of applications where you don't have to trade off privacy with personalization. Let’s redefine personalised experiences, together. ### Grant Categories #### 🛠️ Small Grants (Up to $2,500 USD) **For**: Early-stage projects, prototypes, or short-term experiments.\ **Ideal Applicants**: Individuals, small teams, researchers, and non-profits.\ **Requirements**: * Demonstrate integration of **Persona Protocol** (e.g., using context artifacts or user repositories). * Projects must align with our mission to enhance privacy and personalization. **Example Projects**: * Build a Chrome extension that lets users share context artifacts (e.g., "reading habits" from Google Docs) with news apps. * Create a context model to infer DAO participation credentials from Discord activity. * Prototype an AI agent that uses RAG embeddings from a user repository for personalized recommendations. #### 🚀 Open Grants (Up to $10,000 USDC) **For**: Ambitious projects driving protocol adoption or unlocking novel use cases.\ **Ideal Applicants**: Teams with a track record of execution and clear milestones.\ **Focus Areas**: * **AI & Agents**: Privacy-first AI tools using context artifacts (e.g., agentic workflows for personalized health/fitness). * **Identity & Reputation**: Decentralized identity systems, sybil-resistant mechanisms, or reputation graphs. * **Storage & Tooling**: Enhance user repositories (e.g., ZK-proof storage adapters, query engines for context artifacts). * **Community Growth**: Developer tools, SDKs, or educational content to onboard builders. **Process**: 1. Submit a proposal via GitHub with technical specs, timelines, and budget. 2. Iterate with the Persona team for feasibility review. 3. Milestone-based payouts upon delivery. # Infrastructure Partners A list of infrastructure partners & tools.
Lit ProtocolOswcpR_W_400x400.jpg
Nillion ProtocolAdOJJAHw_400x400.jpg
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# Case Studies # Personal AI Scaled to Thousands of Users through Intract Protocol {% hint style="info" %} Coming Soon {% endhint %} # How Analog leveraged ‘Proof of Humanity’ to remove millions of bots {% hint style="info" %} Coming Soon {% endhint %} # Linea's 250% TVL Growth With Intract’s Targeted Quests Platform {% hint style="info" %} Coming Soon {% endhint %} # Get Involved If you wanna talk, we can jump on a call anytime anywhere for you! {% hint style="info" %} Coming Soon {% endhint %} # Overview Own Your Data, Own Your Future *Welcome to the revolution.*
Today, the coolest new AI agent are getting super personal. They are smart, extremely intuitive and can give you super-personalized intelligent responses. This is awesome until you realise that to deliver these super personalised experiences, they need access to your personal data. This sounds like a bummer, right? Let us break it down for you where you don’t need to sacrifice your privacy. Imagine a world where your data isn’t aloof in corporate servers sitting idle and is providing value to you. This is where we step in with our **Persona Protocol**, breaking down the barrier between Web2 and Web3 and giving you more control. **Why?** Your digital footprints is scattered across different mediums like - X (Twitter), Transactions, Discord Chats & Google Documents. Right now, they are telling your story differently. This is not something we would want? What if we told you can own your story and keep it consistent. This is where we making it real. With Intract’s **Persona Protocol** we are transforming all your scattered digital footprints and giving you full control of how can manage your story on the Internet. #### Unleash Your Digital Superpowers 1. **Be the CEO of Your Data** \ Connect any platform—Twitter, Ethereum, Google, Discord—and transform raw noise into AI-ready context artifacts. Build your social graphs, identity proofs, RAGs, and more. No middlemen. No BS. 2. **Interoperable AI Integration** \ Imagine AI agents that learn from your curated insights to deliver personalized responses—without ever exposing your raw data. Whether it’s our conceptual agents or any AI in the ecosystem, the power remains in your hands. 3. **Privacy as a Priority** \ With military-grade secure enclaves and zero-knowledge proofs, your raw data is always locked down. We process everything within a fortress of privacy, ensuring your secrets stay secret. #### The Future Starts Now Getting started is easier than tweeting: 1. **Plug In:** Connect your first account in just 30 seconds. 2. **Craft Your Story:** Transform your data into dynamic context artifacts. 3. **Unlock Possibilities:** Share insights with apps that respect you. 4. **Claim Your Rewards:** Watch your points stack up. This isn’t just another protocol—it’s a movement. It’s a shift from being mere users to true owners, from data serfs to data sovereigns. The internet’s next era is here, and you’re holding the keys. Ready to rewrite the rules?\ Let’s f\*\*king go. # Connecting Accounts This is the front door to bring all your digital pieces together. When you link all your different accounts, you’re pulling all those scattered pieces of your online life into one safe, easy-to-manage place on the internet that you can control ### Supported Account Types * **OAuth-Based Accounts:**\ Easily link platforms like Twitter, Discord, and others using simple, secure OAuth authentication. * **Blockchain Wallets:**\ Connect your blockchain identities, including Solana and EVM-based wallets, to integrate your decentralized data. * **API Key-Based Integrations:**\ For services that use API keys, just enter your key to establish a connection. * **Upload-Based Sources:**\ For data that doesn’t have direct integrations, manually upload your information to add it to your digital story. ### How It Works 1. **Access the Accounts Section:**\ Log into your user portal and navigate to the Accounts section where you can view and manage all your connections. 2. **Select and Connect Your Platforms:**\ Choose the platform you’d like to connect and follow the on-screen instructions. The process will vary depending on the type: * **OAuth-based:** Redirected to the platform’s authentication page. * **Blockchain Wallets:** Connect using wallet interfaces. * **API Key:** Enter your unique API key. * **Upload:** Manually select and upload your data file. 3. **Data Synchronization:**\ Once connected, we begin syncing your data from each platform to your secure storage: * **Real-Time Streaming:** Some platforms provide live updates. * **Scheduled Syncing:** Others may sync daily or on a set schedule. 4. **Review Your Data Artifacts:**\ After syncing, view a clear list of data artifacts fetched from each connected account. This transparency ensures you know exactly what data is being integrated into your profile. # Data & Storage Your digital story is made up of all sorts of data and it is all over the place. Some of it is structured while some of it dynamic and unstructured. To handle all of these diverse needs, our platforms has a unified database that’s managed for you that can handle all sorts of storage needs you throw at it. ### A Unified Storage Solution No matter what kind of data you’re dealing with—vector embeddings, knowledge graphs, SQL-style structured stuff, or unstructured things like MongoDB docs and S3 storage—we’ve got your back. Our managed database is built to tackle it all. * **Vector databases:** To handle the vector embeddings smoothly * **Knowledge graphs:** To map out all the connections in your data * **Structured Data**: SQL-like tables for the classic organized info * **Flexible Storage**: For anything that doesn’t fit the usual mold. You’re all set with us. **All-in-One, Developer-Friendly:** We’ve combined all storage options and rolled them into one smooth, seamless system. Developers can just add their data into our managed database with ease. ### Your Data, Fully Under Your Control **Privacy and Security First:** Every single piece of your data that is stored in our databases is encrypted with a private key - meaning you are the only with full access to it **Custom Integrations:** If you prefer using your own setup, you’re free to connect your vector database, MongoDB, Ceramic DB. **Comprehensive Data Coverage:** Not only is your raw pieces of data stored here but also the insightful interpretations of your data artifacts stored safely. # Managing Permissions Your privacy and control over your data is as important for us as important it is for you. We take this extremely seriously and we are not joking. This is where we disclose everything about how others can access your data which is only after you give permission to access it. ### What You Can Do 1. **Check Permissions**\ You can see a list of all the apps you've allowed to use your data. It shows which app has access, what kind of data they can take, and when you gave them permission. 2. **Look at Logs**\ You can check records that show when your data was used, what was taken and other such details. This helps you know exactly how your data is being handled. 3. **Change or Stop Permissions:**\ If you don’t want an app to have access anymore, you can simply take it away. You can also adjust permissions to control what you’re sharing. ### **How It Works** When an app uses our system, it starts a process where you decide if it can use your data. You give it permission, and the app gets a special key to access certain things, like your context artifacts.\* Here’s what happens: * **You Say Yes:** You agree to let the app use some of your data. * **App Gets a Key:** It gets a secure key to access only what you allowed. * **Keeping Track:** Everything the app does with your data is recorded, so you can check it anytime. * **You’re in Charge:** You can stop or change the app’s access whenever you want from your dashboard. # Building Context Artifacts Once you’ve connected your accounts and given access to us, we’ll turn it into something cool - Context Artifacts. These are basically snapshots of who you are online. This is what forms the basis for providing you personalised insights ### **The Context Marketplace** The Context Marketplace is a place where you can pick from ready-made insight packages to turn your data into something useful. For example: * **PoH Score:** Shows how active and influential you are online. * **Coding Style Analysis:** Spots patterns in how you code. * **Social Media Persona:** Reveals the vibe of your social media posts. With a couple of clicks, you can add these to your data and get a clearer picture of yourself! ### **Why Build Your Data Story?** 1. **Cool Perks**\ Making your digital profile better means things get more personalised for you—and you get rewards for being active with us. 2. **Get Ready for New Stuff**\ We’re working on **pluggable widgets**—think of a dashboard showing things like your money stats or favorite bookmarks, all pulled from your context artifacts. 3. **You’re in Charge**\ Your insights stay safe in your own storage. You can check, change, or delete them whenever you want, so your digital story is always yours to control. Building your context artifacts is an easy way to make your online world more personal. Pick the insights you like, add them with a click, and see your unique story come to life—tailored just for you! ### **How It Works** 1. **Pick Your Insights** Choose the insight packages you like. Once you add them, they start working with your data right away. 2. **Keeps Getting Better** Your insights update as new data comes in—whether it’s instant or on a schedule—so your profile keeps improving. 3. **Integrated easily** When an app needs your data, these context artifacts are ready to go, making everything personal and easy. # PAL, Your Personal Data Agent PAL is your personal AI helper! It's built to put you in charge and make the most of your data in AI economy. ### The PAL Advantage **Your Data, Your Control:** PAL runs on your device or in a secure environment we provide, keeping your data safe and in your hands. It uses a smart system to turn your tweets, transactions, and chats into useful insights—without sharing your private details. **Sharing Only What You Want:** PAL acts like your personal guard. It knows what data to share and what to keep private, based on your choices. When you use other AI tools, PAL gives them just the right info to make their responses fit you perfectly. **Working Together with Other AIs:** PAL connects you to other AI tools smoothly. While you chat with them, PAL pulls the right details from your data to make every answer spot-on—all while keeping things secure. **Putting You in Charge of AI:** With PAL, you’re not just using AI—you’re helping shape it. You keep the value of your data and get services tailored to you, making you the center of the AI world. # Warden: Your Privacy Agent Imagine you join a new app—like one for rides or games. You skip the “Terms & Conditions” because it’s long and boring. But buried in there, the app gets permission to grab your emails, watch what you browse, or share your location with others. Soon, you’re hit with annoying ads or weird emails. Sound like something you’ve seen? You’re not alone. **More than 60% of people** don’t read those terms, but in 2022, **almost 422 million personal records** got exposed in data breaches (says the Identity Theft Resource Center). It’s not just spam—sometimes it’s serious stuff like your address, credit card, or even doctor records getting out ### What Warden Does **Reads Terms for You:** Warden quickly scans the confusing “Terms & Conditions” and tells you simply: “This app wants your contacts and location all the time. Okay with that?” If you say “No,” Warden stops it for you. **Stops Old Apps:** That budgeting app you forgot about? It might still be snooping on your bank. Warden finds these sneaky connections and lets you cut them off fast. **Checks the Dark Web:** If your password or credit card info is being sold online, Warden warns you right away—no waiting until weird charges show up. **Easy Privacy Check:** Warden gives you a clear list of who’s using your data. If something looks off—like a game tracking your location—you can stop it with one tap # Points System Earn Rewards as You Build Your Digital Story {% hint style="info" %} Coming Soon {% endhint %} # How we handle privacy At Persona Protocol, your privacy isn’t an afterthought—it’s the foundation of everything we do. We believe your data is your kingdom, and only you should hold the keys. **Your Private Key, Your Kingdom:**\ Every piece of data is encrypted with your unique private key, which lives securely in your browser or keychain. This means your raw data is never exposed—not to us, and certainly not to anyone else. Even if you connect multiple accounts (like Twitter and GitHub), we can never tell if they belong to the same person. **Cutting-Edge Security Technologies:**\ We’ve armed our platform with the most advanced privacy-preserving tools available: * **MPC (Multi-Party Computation):** Enables secure processing by splitting tasks across multiple parties without revealing the underlying data. * **Zero-Knowledge (ZK) Proofs & ZKTLS:** Verify transactions and data authenticity without exposing any sensitive details. * **TEE (Trusted Execution Environment):** Provides a secure enclave for computations, ensuring that your private data remains confidential even while being processed. **No Backdoors, No Secrets:**\ Our system is engineered so that only you have access to your personal data. We can’t see it, link your accounts, or share your information. It’s all encrypted, secure, and entirely under your control. With Persona Protocol, you’re not just getting powerful digital tools—you’re getting complete, uncompromised privacy. Your data stays yours, locked down tight with state-of-the-art encryption and security protocols. # FAQs
How do I connect my data? Simply link your favorite platforms—Twitter, Google, Discord, Ethereum, and more—with just a few clicks. Once connected, your data is encrypted using your private key, ensuring that your personal story stays secure and under your control.
How does the points program work? Every time you connect an account or curate your digital story into meaningful insights, you earn points. These points reflect the real value of your digital contributions and can be redeemed for exclusive benefits and advanced features within our ecosystem. It's our way of rewarding you for owning your data.
How is my data kept private? Your privacy is our top priority. Every piece of data is encrypted with your unique private key, which lives securely in your browser or keychain. We use advanced technologies like Multi-Party Computation (MPC), Zero-Knowledge (ZK) proofs, ZKTLS, and Trusted Execution Environments (TEE) to ensure that your raw data is never exposed—and we can never link your different accounts.
What does it mean to control my data? It means you’re in charge. Only you hold the keys to your raw data. We never store or share your personal details without your permission. You decide what gets shared and when, ensuring full ownership and control over your digital identity.
What future features should I look forward to? We're just getting started. Expect more advanced AI integrations, enhanced ways to transform your data into valuable insights, and even more opportunities to earn rewards. The future is personal, and it’s all designed to give you complete control over your digital experience.
Got more questions? Reach out—we’re here to help you own your data and redefine what it means to be truly empowered in the digital age.