⌕01
Search by meaning
Dense vector retrieval finds semantic relationships instead of relying on exact keywords.
OPEN SOURCE · RUST · AI INFRASTRUCTURE
SEARCH
MEANING.
Oriel is a semantic search engine for AI applications. Turn embeddings into a fast, filterable retrieval layer, powered by Rust.
RUST
Memory-safe core
VECTOR
Semantic retrieval
API
Simple integration
THE PLATFORM
The retrieval layer between your data and your AI.
Keyword search tells you what matches. Semantic search helps you discover what belongs together.
≡02
Filter with context
Attach structured payloads to vectors and narrow retrieval with rich conditions.
↯03
Rust-speed core
A memory-safe Rust foundation designed for predictable performance and low latency.
▣04
Deploy anywhere
Run locally, in containers, or wherever your AI stack already lives.
HOW IT FITS
A small engine for a much bigger AI stack.
01
EMBED
Your encoder turns content into vectors.
02
STORE
Oriel keeps vectors with optional payload metadata.
03
QUERY
Search using semantic similarity and filters.
04
RETRIEVE
Your AI system receives the most relevant context.
QUICKSTART
From zero to search.
TERMINAL
$ git clone https://github.com/ATLURI0001/Oriel.git
$ cd Oriel
$ cargo build --release
$ cargo run --release
# or run it with Docker
$ docker build -t oriel .
$ docker run -p 6333:6333 oriel