Verida provides a decentralized data platform that enables users to securely manage their personal data and credentials through confidential compute and encrypted storage. This technology addresses the fragmentation of private data across third-party systems, ensuring that sensitive information remains protected while allowing AI models to access necessary context for personalized experiences.
Funding
$5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
AI models require access to vast amounts of user data to deliver personalized experiences, but this data is often fragmented across various third-party systems, making it difficult to access and raising significant privacy concerns. Current AI platforms have full access to user prompts and training data, creating risks of intellectual property leakage and exposure of sensitive information.
Solution
Verida provides a decentralized infrastructure that enables private AI through secure data management and confidential compute. The platform allows users to connect their private data from various sources to AI models and agents while maintaining complete control and ownership. Verida's Private Data Bridge facilitates the extraction and encrypted storage of personal data, while confidential compute environments ensure data is protected during processing. This approach allows developers to build personalized AI applications without compromising user privacy or introducing data compliance risks.
Target Audience
The primary target audience includes AI developers and businesses seeking to build personalized AI applications while ensuring user data privacy and compliance, as well as individuals who want to control and monetize their personal data.
Features
- Private Data Bridge for secure extraction and storage of personal data from centralized platforms
- Confidential compute environment to protect data during processing by AI models
- Verida Vault for users to manage and control their personal data
- Data Connectors to integrate with various platforms like Google and Telegram
- Standardized data schemas to ensure data is easily digestible by LLMs
- Developer APIs for accessing private user data with valid access tokens
- End-to-end data encryption to protect data in transit and at rest
- Decentralized identity to give users control and eliminate centralization