Verida Vault FAQ
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The Verida Vault provides a secure, user-controlled space for managing personal and private data. All information stored on the Vault is encrypted and stored privately on the Verida Network, ensuring users maintain complete ownership and privacy.
Users can pull data from platforms like Google and Telegram directly into the Vault, with more data connectors from centralized platforms coming soon for various use cases, including private AI.
You can connect and pull data from platforms like Google, including emails, calendars, and Google Drive, as well as data from Telegram. In the future, more data connectors will be added, allowing you to reclaim even more.
All pulled data is securely encrypted and stored in your personal Verida Vault, allowing you to connect this data with a Private AI assistant for a personalized experience or use the data as you see fit.
Go to the , scan the QR code to access Verida Vault, and navigate to the āConnectionsā tab. Select the platform you want to pull data from, like Google or Telegram. Click āConnectā and follow the prompts to authorize the connection. Allow some time for the data to synchronize and be securely stored on the Verida Network. Note: The Verida Vault is in private alpha and available to early testers.
The deletion feature is not currently available in the Vault. However, it is planned for a future release, allowing users to delete specific parts of their data directly from the Verida Vault.
After your data is pulled into the Vault, deletions made on connected platforms (e.g., deleting an email in Gmail) will not be reflected in the Verida Vault. This feature is not currently supported but is planned for future updates.
Verida is committed to adhering to global regulatory standards, such as GDPR, to ensure usersā rights to data privacy and portability. The Verida Network is designed to comply with these regulations, giving users full control over their data and the power to decide how it is utilized.
The Private Data Bridge is a core infrastructure that allows users to extract and store their personal and private data from centralized platforms. It enables secure access to this data for various use cases, such as private AI. The bridge ensures that all pulled data is encrypted and securely stored on the Verida Network, giving users complete ownership and control over their information.
The Verida Vaultās AI Assistant securely accesses your personal and private data to deliver highly tailored responses. It combines data stored in your Verida Vault with publicly available data from large language models (LLMs). The more relevant data you store in your Vault, the more accurate and personalized its responses will be, delivering a truly customized experience for you.
The Vaultās AI Assistant can access data stored in the Verida Vault, enabling it to provide highly personalized responses based on private user-owned data.
All personal and private data remains securely stored and processed on the Verida Network, with access controlled by your private key. The AI Assistant uses this data exclusively to deliver accurate and customized responses while maintaining your privacy.
Your data is not currently processed within a Verida Confidential Compute secure enclave. Secure enclaves do not yet support GPU access, which is essential for efficient LLM operations.
In the future, Vaultās AI Assistant will process your data within secure Trusted Execution Environments (TEEs). Your data will remain securely stored on the Verida Network and be confidentially processed through the Verida Confidential Compute secure enclave.
The Private Data Bridge empowers users to pull and take full control of their personal and private data from Web2 centralized platforms like Google and Telegram, with additional data connectors planned for the future.
This data can then be seamlessly integrated into hyper-personalized solutions such as AI assistants, as well as future services and products like data marketplaces and other innovative use cases.
For the moment, you canāt customize which data the AI can or cannot access. Once you synchronize your data from Google and/or Telegram, it can be utilized by the AI to personalize responses for you.
Controlling which data is used for a given assistant or question is a feature we want to work on in the future.
Developers can contribute to Verida in several ways:
Note: These APIs are in private alpha and accessible to early builders.
Weāve launched the , which rewards developers with $VDA tokens for creating new data connectors. You can view and vote on the to prioritize the connectors you need. This initiative aims to expand available connectors and enhance data transfer capabilities on the Verida Network.
It also allows to leverage user data in a secure and privacy-preserving way, enabling the creation of highly personalized products and applications.
The Verida Vault is in its alpha release and provides the option to use or your own LLM. This is a temporary solution as we collaborate with partners to enable LLMs to run efficiently and cost-effectively within secure enclaves.
Your data is encrypted with private keys stored on your device. For example, when you log into a web application, an encryption key is generated in the Verida Wallet and sent to your browser to encrypt and decrypt data. Any data sent to a storage node is pre-encrypted and inaccessible without your key. Unlike other Web3 storage solutions with publicly readable data, the Verida Network provides built-in encryption and access controls (read, write, delete) for enhanced security. For more details, explore the .
Building Data Connectors: The is open source, allowing developers to create new connectors that enable users to pull their data from additional platforms. To encourage contributions, the rewards developers with $VDA tokens for building new data connectors, expanding the ecosystem and empowering users.
Utilizing Verida Private Data APIs: enable applications to CRUD (Create, Read, Update, Delete) data in the Vault. Developers can integrate private user data into their applications, enabling them to query, search, and execute AI requests using user-provided data.
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