Enterprise search returns documents, not understanding
Keyword matches don't tell your teams — or your AI — what a policy or contract actually means.
Knowledge Infrastructure for Enterprise AI
Knowledge that AI can trust
Enterprise information is fragmented across millions of documents. Leyli turns it into explainable, ontology-grounded knowledge that grounds Knowledge Graphs, GraphRAG, and every intelligent system your teams rely on.
Knowledge Graphs
GraphRAG-ready
Ontology-grounded
Explainable by design
Grounded in open standards
OWL / RDF
SKOS
SNOMED CT · UMLS
ChEBI · AgroVoc
W3C PROV
ISO 25012
The problem
Your AI cannot trust disconnected documents
Employees waste hours searching. Experts leave and knowledge disappears with them. AI systems hallucinate because they lack trusted, structured knowledge.
Critical knowledge is trapped in PDFs
Reports, SOPs, clinical notes and manuals are unreadable to modern reasoning systems.
Every department defines the same concept differently
Without shared meaning, AI outputs contradict each other — and compliance breaks down.
LLMs hallucinate without grounded knowledge
Generative AI needs an ontology-aware layer to reason accurately over your business.
Not another chatbot
Leyli is the knowledge infrastructure beneath your AI stack
Not a search engine. Not a graph database. Not a GraphRAG wrapper. Leyli is the explainable knowledge layer that lets every enterprise AI system reason over trusted, structured meaning — with provenance you can audit.
Capabilities
Five outcomes, one knowledge layer
Every capability is designed to deliver auditable, ontology-grounded knowledge — ready for Knowledge Graphs, GraphRAG, and AI agents.
Knowledge Extraction
Turn unstructured documents into entities, relationships, and facts you can trust — with source evidence preserved at every step.
- Extract entities and relationships
- Connect knowledge across documents
- Preserve source evidence
Knowledge Graph
Visualise your organisation's knowledge as an interactive graph and export structured outputs for downstream systems.
- Interactive visualisation
- Discover hidden relationships
- Export structured knowledge
Ontology Integration
Ground extracted knowledge in biomedical, industrial and enterprise ontologies for semantic normalisation across systems and languages.
- Biomedical ontologies
- Enterprise ontologies
- Semantic normalisation
Explainability
Every entity, relationship and answer traces back to its source. Regulators, auditors and domain experts can inspect the evidence at any depth.
- Provenance for every fact
- Evidence traceability
- Audit-ready outputs
AI Integration
Deliver context to LLMs and AI agents through a GraphRAG-ready knowledge layer and structured, machine-consumable APIs.
- GraphRAG-ready outputs
- AI-agent-ready APIs
- Structured JSON & RDF
Bilingual by design
Reason across languages and scripts. Every ontology and knowledge graph is fully bilingual, with equal fidelity in English and Persian — and extensible beyond.
- English & Persian first-class
- Cross-lingual normalisation
- RTL / LTR aware UX
Technology
From enterprise data to intelligent action
Leyli sits between your data and your AI — an explainable, ontology-grounded layer that every downstream reasoning system can rely on.
An architecture built for trustworthy AI
Leyli composes proven components — semantic normalisation, ontology alignment, graph construction, provenance capture — into one coherent knowledge layer. You keep your data. Your AI gains meaning.
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1
Ingest enterprise data Documents, records, structured feeds. Nothing leaves your perimeter.
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2
Extract meaning Identify entities, relationships and evidence with domain-aware models.
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3
Ground in ontology Normalise concepts against curated biomedical, industrial and enterprise vocabularies.
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4
Construct knowledge graph Assemble an explainable, queryable knowledge graph with full provenance.
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5
Serve to AI systems Deliver GraphRAG context, structured answers and evidence to any AI or agent.
Why Leyli
The knowledge layer other approaches never built
LLMs, graph databases and RAG frameworks each solve one piece. Leyli composes them into a coherent, explainable knowledge platform.
| LLM alone | Graph database | GraphRAG framework | Leyli | |
|---|---|---|---|---|
| Structured knowledge from documents | Text in, text out | Requires manual modelling | Partial, chunk-based | Entities, relations and evidence, end-to-end |
| Ontology grounding | None | Optional, DIY | Rare | Built-in biomedical, industrial & enterprise ontologies |
| Explainability & provenance | Opaque | Depends on schema | Chunk-level at best | Fact-level provenance and evidence, W3C PROV-aligned |
| Bilingual & multilingual | Best-effort | Rarely handled | Language-dependent | First-class English & Persian, extensible |
| AI integration | You build it | You build it | Framework-locked | GraphRAG-ready, agent-ready, structured APIs |
Industries
Domain-aware from day one
Leyli composes with curated ontologies tuned to the terminology of each industry — so extraction is precise, and AI outputs are defensible.
Healthcare & Life Sciences
Turn clinical notes, protocols and biomedical literature into a coherent knowledge graph grounded in SNOMED CT, UMLS and ChEBI — ready for clinical AI, research discovery and regulatory review.
Clinical notes→
Ontology grounding→
Knowledge Graph→
Clinical AI
Legal & Compliance
Extract obligations, parties, dates and clauses from contracts and regulations. Build a risk knowledge graph that AI assistants can reason over — with every answer backed by traceable evidence.
Contracts→
Entities→
Obligations→
Risk knowledge
Manufacturing & Industry
Convert maintenance manuals, sensor logs and equipment specifications into an equipment graph — powering predictive maintenance and expert-level assistant answers on the plant floor.
Manuals→
Equipment graph→
Maintenance intelligence
Research & Knowledge Discovery
Ingest publications, datasets and grants. Discover hidden relationships across disciplines and support literature-scale knowledge discovery for research teams and grant-funded programmes.
Publications→
Knowledge discovery→
Graph analytics
See it work
Seven steps from document to explainable knowledge
Our interactive demo walks a real document through the full Leyli pipeline — extraction, ontology grounding, graph construction and evidence — in under two minutes.
1Upload documentPDF, DOCX or plain text
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2Extract entitiesPeople, places, concepts
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3Extract relationshipsMeaningful links
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4Generate graphInteractive knowledge graph
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5Link ontologySemantic normalisation
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6Show evidenceProvenance for every fact
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7Export knowledgeJSON · RDF · GraphRAG
Trust
Designed for enterprise confidence
Research-informed, standards-aligned, and built for organisations that need defensible AI outputs — not black boxes.
Traceable outputs
Every extracted fact links to its source, its span and its ontology anchor.
Curated ontologies
Biomedical, chemistry, agriculture and enterprise vocabularies out of the box.
Languages, natively
English and Persian first-class — with cross-lingual normalisation and RTL UX.
Runs in your perimeter
Deploy in your VPC or on-premises. Your data never leaves your control.
Built on proven research
Grounded in decades of knowledge engineering
Leyli assembles well-studied disciplines — knowledge graphs, ontology engineering, provenance, GraphRAG — into a coherent enterprise platform.
GraphRAG & retrieval-augmented reasoning
Grounding LLMs in structured graphs measurably improves factuality and traceability over vector-only RAG.
Knowledge graph foundations
Decades of research show that entity-centric graphs are the durable substrate for enterprise semantics.
Ontologies & semantic interoperability
Shared vocabularies (SNOMED, UMLS, ChEBI, AgroVoc) enable cross-system reasoning at scale.
Explainable AI
Regulators and users increasingly demand traceable, evidence-linked AI outputs.
Provenance (W3C PROV)
Open standards for tracking the origin and derivation of every knowledge assertion.
Enterprise knowledge management
Research consistently identifies knowledge fragmentation as a top-three barrier to enterprise AI adoption.
What Leyli does
Unstructured information becomes knowledge ready for AI
Explainable knowledge graph
Ontology-grounded
Evidence-linked
Extract entities and relationships · connect knowledge across sources · ground in domain ontologies · trace every insight back to its original evidence
Get in touch
See Leyli on your own knowledge
Bring a document, a corpus, or a challenge. In one session we'll show you how Leyli grounds your information into an explainable knowledge graph — and what it unlocks for the AI systems you're building today.