Natural language substrate with formal semantics. Build knowledge graphs, power AI communication, and structure semantic data. For Humans and Robots Alike.
Alice person knows Bob person .
Bob knows Charlie.
Alice has age = {30}.
Bob has age = {25}.Designed from the ground up for error prevention, natural expression, and seamless human-AI collaboration.
Reduced syntax with multi-level validation eliminates common errors. Type inference without explicit declarations.
Natural language substrate reduces ambiguity. Perfect for AI agents, chatbots, and multi-agent systems.
Decentralized identity, verifiable credentials, and cryptographic signatures built-in. W3C DID Core compliant.
Familiar query patterns with 75% fewer errors. Easy migration from existing graph databases.
~15 core constructs vs SPARQL's 50+. Multiple equivalent syntaxes for flexibility.
Replace JSON/XML with semantic format. Works with knowledge graphs, semantic web, and data exchange.
From simple statements to complex structures with DID protection.
Alice person knows Bob person .
Bob knows Charlie.
Alice has age = {30}.
Bob has age = {25}.Same power, dramatically simpler syntax.
PREFIX foaf:
SELECT ?person ?friend WHERE {
?person a foaf:Person ;
foaf:knows ?friend .
?friend foaf:based_near ?location .
?location geo:name "Paris" .
} person person knows friend person .
friend based_near location place .
location name = {Paris}.| Metric | Kyl vs SPARQL | Kyl vs Cypher |
|---|---|---|
| Error Reduction | ~75% fewer | ~40% fewer |
| Syntax Simplicity | ~60% simpler | ~40% simpler |
| Learning Curve | ~80% faster | ~50% faster |
| Natural Language Proximity | 10x closer | 5x closer |
From knowledge graphs to AI agents, Kyl powers the next generation of semantic applications.
Human-AI & AI-AI communication
Error-free data ingestion
HIPAA-compliant records
Legally binding documents
Everything you need to start writing Kyl.