XTrace SDK documentation¶
What is XTrace?¶
Traditional vector databases require you to hand your data to a third party in plaintext. XTrace is different: your document content is AES-encrypted and your embedding vectors are homomorphically encrypted before they leave your machine. The server stores and searches over ciphertexts — computing nearest-neighbor Hamming distances directly on encrypted vectors — without ever seeing the underlying data. When results come back, you decrypt them locally.
This means you get semantic search with the same privacy guarantees as if the data never left your laptop.
The SDK has two modules: x-vec for encrypted vector search, and x-mem for encrypted agent memory (coming soon). Both share the same credentials, execution context, and XTrace integration.
Getting started¶
Note
Create a free account at app.xtrace.ai to get your API key and org ID. The free tier is rate-limited but fully functional.
Choose your path:
Python SDK — Installation then x-vec Tutorial for a concept-first walkthrough with full code examples.
CLI — Installation then XTrace CLI Quick Start for a terminal-first workflow that gets you querying in four commands.
Getting Started
CLI
Reference
API Reference