A simple, intuitive API
Go from connection to semantic search in four steps, in the language you already work in.
pip install ahnlich-client-pyimport asyncio
from grpclib.client import Channel
from ahnlich_client_py.grpc.services.ai_service import AiServiceStub
async def main():
async with Channel(host="127.0.0.1", port=1370) as channel:
client = AiServiceStub(channel)
# ready to talk to Ahnlich
Everything you need to ship semantic search
One fast, open-source engine that handles it all: embed, index, filter, and retrieve, so you can focus on your product, not your infrastructure.
Blazing fast
A lock-free, in-memory core built in Rust with SIMD-accelerated similarity search for low-latency retrieval at scale.
Read moreAI built in
A first-class AI proxy runs ONNX embedding models for you. Send raw text or images and let Ahnlich handle the vectors.
Read moreHybrid search
Combine semantic vector search with structured metadata predicates to filter results with surgical precision.
Read morePluggable models & metrics
Bring your own embedding models and choose the similarity metric (cosine, Euclidean, dot product) per store.
Read moreDurable by design
Snapshot persistence with deterministic hashing keeps your data consistent across restarts and upgrades.
Read morePolyglot clients
gRPC and Protocol Buffers power native SDKs for Rust, Python, and Node.js so you can build in any stack.
Read moreUp and running in seconds
Install a single binary and start indexing. No cluster to babysit, no heavyweight dependencies. Just a fast vector store ready for your embeddings.
# Run the Ahnlich DB server
cargo install ahnlich_db
ahnlich_db run --port 1369
# ...or spin up the AI proxy for automatic embeddings
cargo install ahnlich_ai
ahnlich_ai run --port 1370Start building smarter search today
Grab a release for Mac or Linux, or build from source. Ahnlich is free and open source with an active community.