// summary
Thunderbolt is an open-source, cross-platform AI client designed for on-premise deployment and data ownership. It supports a wide range of frontier, local, and on-premise models across desktop and mobile environments. The project is currently under active development with a focus on enterprise readiness and security.
// technical analysis
Thunderbolt is an open-source, cross-platform AI client designed to provide users with full control over their models and data, effectively eliminating vendor lock-in. By supporting both local and on-prem deployments, the project addresses the critical need for enterprise-grade privacy and data sovereignty in AI workflows. The architecture prioritizes flexibility, allowing integration with various model providers while maintaining a consistent user experience across desktop and mobile environments.
// key highlights
// use cases
// getting started
To begin using Thunderbolt, developers should refer to the deployment documentation to set up the backend using Docker Compose or Kubernetes. Once the backend is running, users can connect their preferred model providers, such as Ollama or OpenAI-compatible endpoints, through the application settings. For those interested in contributing or local testing, the development guide provides instructions for setting up the environment and running the project locally.