Leyli
PUBLIC BETA BIOMEDICAL KNOWLEDGE ENGINE DEMO

See how Leyli turns biomedical documents into trusted AI-ready knowledge.

Watch the short tutorial, then launch the live demo to load documents, select UMLS and SNOMED CT, analyze biomedical text, inspect evidence, explore the knowledge graph, generate GraphRAG context, and export machine-readable outputs.

ExtractEntities, relations, semantic types, and source evidence.
GroundUMLS and SNOMED CT concept context for biomedical terms.
ExploreKnowledge graphs, communities, entity details, and GraphRAG packages.
Run Biomedical Demo Explore Technology
Short tutorial Load documents, run analysis, inspect evidence, graph knowledge, GraphRAG, and exports.
WHAT YOU WILL SEE

A complete Knowledge Engine workflow, not only extraction.

The live demo shows how biomedical documents become structured, inspectable, ontology-aware, graph-native knowledge that can support trustworthy LLM, GraphRAG, and agent workflows.

Source TraceabilityEntities, relations, answers, and graph facts stay connected to source text.
Ontology ContextBiomedical concepts can be linked to UMLS and SNOMED CT metadata.
Knowledge GraphNodes, labeled edges, communities, neighborhoods, and detail popups make knowledge inspectable.
AI DeliveryGraphRAG packages, annotations, exports, ETL outputs, and API-ready structures prepare knowledge for other systems.
WHAT THIS DEMO PROVES

Complete knowledge-engine pipeline for trustworthy AI.

The Biomedical Demo is a working proof that documents can become structured, evidence-backed, graph-native knowledge for LLMs, GraphRAG systems, agents, and downstream applications.

Structured KnowledgeDocuments can become structured, inspectable knowledge.
Ontology GroundingOntologies reduce ambiguity and improve concept grounding.
Explainable GraphsKnowledge graphs make relationships visible and explainable.
GraphRAG DeliveryGraphRAG packages provide grounded context for LLMs and agents.
Source EvidenceSource evidence keeps AI outputs auditable and trustworthy.
Domain AdaptationThe same engine can be adapted beyond biomedicine to legal, finance, retail, manufacturing, and enterprise knowledge domains.
WHY BIOMEDICAL FIRST

Medicine is a demanding proof point for trustworthy knowledge infrastructure.

Biomedical knowledge requires precision, terminology, source evidence, ontology grounding, and explainability. The demo shows Leyli handling these requirements in one of the world's most complex knowledge domains.

Documents become structured knowledge

Clinical and biomedical text becomes entities, relations, semantic types, and reusable knowledge objects.

Proven in demo

Ontology grounding

Biomedical concepts can be linked to UMLS and SNOMED CT for clearer meaning and semantic context.

Proven in demo

Knowledge graph generation

Extracted knowledge becomes an inspectable graph of connected concepts, paths, and communities.

Proven in demo

Evidence preservation

Entities, relations, graph facts, and GraphRAG context stay connected to source evidence.

Proven in demo
Biomedical Document Knowledge Extraction Ontology Grounding Knowledge Graph Evidence GraphRAG Enterprise AI
DOMAIN-INDEPENDENT ENGINE

If it works for biomedical knowledge, it can work for enterprise knowledge.

Leyli starts with biomedicine because the domain makes accuracy, traceability, and terminology visible. The same Knowledge Engine pattern can be adapted to legal, finance, manufacturing, retail, education, government, and other knowledge-heavy domains.

The Biomedical Demo is the first proof of a domain-independent Knowledge Engine.

READY TO TRY IT?

Launch the live Biomedical Demo.

Use a sample document or bring your own biomedical text, then inspect the generated knowledge layer.

Run Demo