From Taxonomies to GraphRAG
Organize, Categorize, and Discover Enterprise Knowledge
Taxonomies and Ontologies
Use a no-code enterprise taxonomy and ontology management system to model any business domain as an inference-bearing knowledge graph. Standardize enterprise terminologies in taxonomies and capture how entities are described and related in machine-intelligible knowledge models, or ontologies.
Classification and Extraction
Use auto-classification for known entity extraction (inline tagging) and document level classification, automating the capture of concept-to-content annotations and generating a continuously evolving, content-aware knowledge graph.
Semantic Knowledge Graph
Adhere to industry standards including ISO 25964 and W3C RDF, SKOS, and OWL to semantically represent enterprise information, enabling knowledge graphs that are machine-intelligible, inference-bearing, and capable of knowledge generation.
GraphRAG
Guide the data retrieval process in RAG-enabled generative AI to enhance accuracy, ensure that all relevant information is identified, processed, and validated, and improve the overall quality of generated insights and automated workflows.
The Synaptica Guide
Download the Synaptica Guide to Developing Enterprise Ontologies, Taxonomies and Knowledge Graphs. Our 5th edition includes a new section on RAG and GraphRAG.
Enterprise Taxonomy Management and Knowledge Graph Systems
Design, build and manage with speed
Intuitive drag-and-drop graphical user interface and workflow.
Simplify systems integrations
Adopt open industry standard models and data interchange formats.
Build smarter search and discovery
Leverage logical dependencies defined by properties, predicates and classes.
Create KOS schemes
Use public domain ontology plug-and-play predicates and classes.
AI Studio
Automate semantic tagging and auto-categorization of enterprise content.
Squirro AI Studio enables taxonomists and content managers to automate the tagging and categorization of enterprise content.