Enchanted is a personal AI interface focused on privacy. Its goal is to leverage the most advanced models while ensuring that user identity and data has every possible protection. Design decisions in Enchanted prioritize the ability to access the best capabilities while being at the privacy pareto frontier. While the official release of Enchanted is opinionated about features, models, and integrations, developers can use the open-source version of Enchanted for greater flexibility. Enchanted screenshot Enchanted screenshot

​
Models

Enchanted relies on a variety of models.

Completions Model

Use open-source models (Ollama, vLLM, llamacpp) or closed-source models compatible with the OpenAI API. Completions model is used for chats, memory and handling the agent.

Embeddings Model

Choose from open-source (Ollama), closed-source, or local embeddings. Enchanted comes packaged with a open soruce, local embeddings model (JinaAI) running on the ONNX inference engine. Embeddings model is responsible for the agent memory and semantic search.

Anonymizer Model

The Anonymizer enables you to use advanced models like GPT-3 or GPT-4.1 by performing semantic replacements on requests using a local model trained to understand PII.

STT

Any model compatible with the OpenAI API can be used for speech-to-text. The official release of Enchanted uses Whisper running in a trusted execution environment.

TTS

Any model compatible with the OpenAI API can be used for text-to-speech. The official release of Enchanted uses the Kokoro model running in a trusted execution environment.

​
Demos

​
Agentic tool use

​
Tasks

​
Gmail MCP

​
Google Drive MCP