Question: Are there any enterprise knowledge graph solutions that can help me connect the dots between different data silos and improve my organization's overall data intelligence?

Ontotext has a broad AI-infused product line that spans data access and data analysis with large-scale knowledge graphs. That includes Ontotext GraphDB, Ontotext Platform, Ontotext Metadata Studio and Ontotext Refine for tasks like data integration, large-scale inferencing, metadata management and data quality. It's used in many industries, and offers professional services and training programs to help customers get the most out of their data smarts.

Neo4j is another popular product for complex data structures, with graph-native scalability, flexible deployment choices and strong security. It's a good fit for knowledge graph projects, and also can be used for data science and machine learning work. Neo4j's performance makes it a good choice for high-performance graph databases for big data and real-time insights.

Franz's AllegroGraph is a high-performance, horizontally scaling graph database that can be used in combination with large language models and vector storage. It's used in industries like health care, financial analysis and life sciences, and products like Gruff for graph exploration and Common Lisp Tools for more advanced applications. Franz also offers professional services to build Enterprise Knowledge Graphs, a good starting point for many uses.