From nothing to a search result
One dependency and no cluster to provision. A new node runs for fourteen days without a licence, so you can reach a result before deciding whether to go further.
Take the quickstart →# Run it
export LUCENIA_INITIAL_ADMIN_PASSWORD="<the password you set in docker-compose.yml>"
docker compose up -d
# Check it
curl -k -u admin:$LUCENIA_INITIAL_ADMIN_PASSWORD "https://localhost:9200/"
Start with what you are trying to do
Search by meaning
Send plain text and let the cluster find the closest matches — no client-side embedding calls, no second service to keep in step.
semantic query →Process your content
Extract, chunk, embed and OCR documents in more than ten formats — PDF, DOCX, HTML, GeoTIFF — on the way in.
ingest pipelines →Work with places
Shapes, not just points. Route by road rather than radius, summarise where data concentrates, and render vector tiles from the cluster.
geospatial intelligence →Give agents memory
A durable remember and recall layer with recency-aware retrieval, per-organisation isolation, and drift anchors.
inference memory →Govern sensitive data
Detect and redact PII, PHI, payment and secret data before it is indexed, against named policies you define.
compliance engine →Run it in production
Docker, Kubernetes with Helm, tarball or Windows — with TLS, attribute-based access control and audit logging.
install and configure →Why teams choose it
It runs where your data is
Every component runs on your infrastructure. Content is extracted, embedded, redacted and searched inside your own trust boundary — including air-gapped deployments.
One engine, not a pipeline of services
Extraction, chunking, embedding, vector and keyword search, reranking and grounding are the same system. There is no separate service to deploy, scale and keep in step with your mappings.
Answers you can defend
Retrieve by a vocabulary you control rather than by an embedding you do not, and carry provenance through to the citation. "The ontology says so" is a reason; "the vector said so" is not.
Looking for something specific?
Every field type, query, aggregation, processor and API is in the reference.