Architecture Patterns
For more than twenty years, we have been building reliable enterprise systems with GraphDB and other semantic technologies. We have found working architectural patterns that can create efficient, scalable, and maintainable enterprise-grade solutions.
Browse through the different architectural patterns you can leverage when designing knowledge graph-powered systems.
Generative AI
Advance your business and unlock new levels of productivity, efficiency, and innovation with GenAI and LLMs. Enrich LLMs with domain knowledge with Graph RAG for accurate, contextually relevant responses and powerful insights.
Enhance LLM with context
Integrate structured and unstructured data (RAG) and set a reliable reference context (Grounding) .
Understand logic behind responses
Ensure traceability and explainability for the sources of the generated answer.
Assess AI risk
AI risk assessment and examination
Capabilities
LLM fine-tuning
Prompt engineering
Graph RAG
Stochastic algorithms evaluation
Domain knowledge graph
Advance your business and unlock new levels of productivity, efficiency, and innovation with GenAI and LLMs. Enrich LLMs with domain knowledge with Graph RAG for accurate, contextually relevant responses and powerful insights.
Build a conceptual model
Unify the meaning of key concepts and vocabulary within the enterprise.
Establish a benchmark
Create a reliable reference data for the organization.
Simplify data governance
Centralize the management, lineage and access to common data assets.
Capabilities
Data reuse/FAIR
Data validation
GraphQL
Chat/NLQ
Ontology management
Inference
Data fabric
Connect all your diverse enterprise data with architecture and technology. Integrate data fabric as a reusable query-able layer that allows access to information across data silos for truly powerful insights.
Consume data with context
Access faster search and reporting by connecting existing enterprise data.
Cut complexity and empower users
Simplify data complexity for users, shifting focus from data management efforts to deriving value from data.
Manage data effectively
Adopt “Data as a product” approach for your business to increase market competitiveness and drive innovation.
Capabilities
Integration with data catalogs
Integration with data management platforms (Databricks, Azure, GCP)
Data virtualization
Data linking
Reporting and BI
GraphQL
Chat/NLQ
Graph analytics
Understand complex relationships patterns and trends in your business data by analyzing it through a data science platform. Get the whole story behind your enterprise information.
Access data easily
Leverage a single graph model optimized for analytics and reporting.
Uncover insights
Generate hypothesis through graph pattern similarity and clustering.
Unlock trends and patterns
Predict and identify patterns based on the network connectivity.
Capabilities
Graph analytics
Data processing
Integration with ML/AI
Graph path search
Semantic content hub
Integrate a semantic content platform built on knowledge graphs to organize various data (research, papers, documents) and analyze relationships, detect patterns, and infer new facts.
Uncover insights
Unlock knowledge hidden into unstructured documents.
Organize enterprise data
Define standard metadata to describe digital assets.
Search and reuse data
Search and navigate unstructured or semi-structured data based on text and metadata.
Capabilities
Data reuse/FAIR
NLP and Information Extraction (IE)
Document taggging (AutoCat)
Meta-data creation and validation
Integration Content Management Systems (CMS)
GraphQL
Chat/NLQ
Taxonomy management
Multi-paradigm search and query
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