Entrova is a decentralized data orchestration layer that secures and optimizes customer data for AI model training using on-chain large language models (LLMs) and user-contributed data. The platform addresses issues of data silos and fragmentation, ensuring user data sovereignty and facilitating a community-governed ecosystem for independent developers.
Funding
Funding not disclosed
Founders
Product
Problem
Training advanced AI models requires vast amounts of high-quality, well-organized data, but customer data is often siloed and fragmented across various platforms, making it difficult to access and utilize effectively. This data fragmentation hinders the development of accurate and reliable AI models, limiting their potential and increasing development costs.
Solution
Entrova provides a decentralized data orchestration layer designed to secure and optimize customer data for AI model training. The platform leverages on-chain large language models (LLMs) and user-contributed data to address data silos and fragmentation. By ensuring user data sovereignty and facilitating a community-governed ecosystem, Entrova enables independent developers to access and utilize high-quality data for training AI models. The platform aims to create a more efficient and transparent data ecosystem for AI development.
Target Audience
The primary target audience includes AI developers, data scientists, and organizations seeking to improve the quality and accessibility of data for training AI models.
Features
- Decentralized data orchestration for AI model training
- On-chain large language models (LLMs) for data processing
- User data sovereignty and control
- Community-governed ecosystem for independent developers
- Secure data pipelines for advanced AI model training