Knowledge Management Suite
The Graphwise Knowledge Management Suite surfaces the entire enterprise knowledge consisting of structured knowledge (spreadsheets, statistics, performance reports) and unstructured knowledge (emails, minutes, policy documents, …). You get more reusable and customizable content providing the full picture and reducing costs by eliminating the need to rewrite, reformat and republish. The Graphwise approach uses automated tagging, natural language processing, semantic search and recommendation together with knowledge graphs to build a rich knowledge infrastructure to deliver knowledge as a service.
Components of the Graphwise Knowledge Management Suite
GraphDB
GraphDB is a semantic graph database for managing large knowledge graphs using RDF and SPARQL. It offers reasoning capabilities and integrates with applications like Elasticsearch for semantic search. Highly scalable, GraphDB supports real-time inferencing and query evaluation under massive data loads. It performs well across on-premise and cloud environments, making it suitable for healthcare and media industries.
Graph Modelling
Graphwise award-winning graph modeling tool delivers 1st class taxonomy and ontology management. It offers an intuitive, centralized platform to create, link, and manage knowledge structures, with generative AI recommendations and easy integration. By structuring and connecting enterprise data, PoolParty transforms siloed information into actionable insights, supporting AI-driven analytics and business growth.
Graph and Text Analytics
A component powered by the PoolParty Extractor Service and Metadata Studio, uses machine learning and natural language processing with knowledge graphs to analyze text deeply, extracting concepts, entities, and even hidden context. It automatically tags and enriches content, resolving ambiguities and supporting semantic search and integration with enterprise systems, so organizations can turn unstructured text into actionable, intelligent metadata for business growth.
Refine
BI semantic layers focus on consistent data views for BI tools, using relational databases and SQL. Knowledge graph semantic layers represent data as interconnected entities, enabling reasoning and discovery via knowledge graph tech like RDF and SPARQL. Combining both leverages their strengths for comprehensive solutions. They aren’t the same concept.
UnifiedViews
PoolParty UnifiedViews is an ETL framework that integrates diverse data into a knowledge graph, supporting RDF and ontologies. It offers a graphical interface for creating data processing pipelines, allowing users to transform data into RDF and perform cleansing and validation. UnifiedViews supports features like SHACL for error detection and SPARQL queries for further data processing.
Transform Data into Knowledge
The suite that enables your knowledge-driven growth
Taxonomy Management
Position
Organize your knowledge and make information easy to find, use and analyze. Benefit from controlled vocabularies, agile metadata, and intelligent content.
Connect the dots across your IT systems
Position
- A data fabric to gain unified access to your structured data.
- Semantic models to search and recommend
- Uncover new relationships with reasoning.
Data Governance
Position
Successful metadata management is based on a solid data governance process and uses metadata standards that ensure consistency of processes along the different activities.
Graph NLP
Position
The most precise method to create knowledge from unstructured data. Extract relevant terms from a text with a tool that is able to disambiguate language discrepancies and the context of document.
Concept Tagging
Position
Benefit from highly customizable and precise automated tagging and classification. Tag your documents to prepare them for semantic search and recommender systems.
Ontology Management
Position
Make meaning with expressive data connections. If the business case demands higher expressivity, such as pharma or finance, we extend our models with custom schemas and work with ontologies.
Highlighted features included in the Knowledge Management Suite
Taxonomy Advisor
Speed up the taxonomy creation process and improves its enrichment by using LLMs to generate narrower concepts and alternative labels. The LLM is integrated with PoolParty so the suggestions can be added easily to the taxonomy.
Inferencing
Inferencing makes it possible to discover documents by uncovering implicit concepts – i.e. the facts that would otherwise be hidden. Inference apply rules to the existing dataset to generate new knowledge connections.
Linked Data Enrichment
Using linked data and corpora, users can add concept into the taxonomy tree. You can use thisr to derive a set of concepts that share the same relation as narrower.
Entity Extraction
The Graph NLP ExtractorI enables you to do highly precise entity extraction based on a rich set of parameters. The API services can be used instead of SPARQL queries and make semantic technologies accesible to developers with a broad skill-set.
Workflow Management
Graphwise provides effective workflows for the approval of new concepts in a collaborative project setting. The suggested concept dashboard allows the knowledge engineer to keep track of suggestions and encourage review processes in a streamlined manner.
Quality ensurance
- Monitor the progress of a pipeline
- Extensive debugging tools to improve data at any point of the pipeline
Knowledge Retrieval
Graph Search and Recommendation is an out-of-the-box solution for document search and visual analytics. . Graphwise Knowledge Retrieval combines the power of graph databases with features of ‘traditional’ search engines like Elastic Search.
Lab and Workbench
The Workbench is designed to make a knowledge retrieval system easily configurable. In the Workbench, the user toggles various levers to specify which aspects of the knowledge model the system should draw on.
Services:
Access to the Graphwise Help Desk
Detailed Help documentation
Best Practice Configurations:
Once you have decided to use Graphwise it is time to find the configuration that best suits your needs. A key to this is the so-called multi-tiering, which is the use of Graphwise licenses on a distributed infrastructure.