Dynamic Knowledge Graphs

Like many organizations, we at VisualVest face the challenge of distributed and constantly evolving knowledge sources. Documentation lives across repositories, internal wikis, JIRA tickets, and various file formats in cloud storage. With ~250 employees making daily changes, our source of truth is highly dynamic. While traditional document-based RAG using semantic embeddings solved some of these pain points, it couldn't answer holistic questions or understand relationships between sources, leading us to explore graph-based approaches.

The challenge? Real-world knowledge sources are inherently dynamic. When thinking about information management and retrieval, we cannot ignore this reality if we want to create powerful, machine-readable and actually useful products. Microsoft's popular GraphRAG library explicitly rejected dynamic features (like deletion) due to complexity concerns. However, we believe that constantly rebuilding entire graphs isn't feasible for production systems.

This talk presents our solution: a truly dynamic knowledge graph with full insertion, query and deletion capabilities. We are also working on reducing the high computational cost of building knowledge graphs. Through caching strategies and small language model fine-tuning, we are trying to minimized both computational effort and strengthen our independence from cloud providers.

What you'll learn: - An industry perspective on the challenges of distributed knowledge sources - Formal definition and properties of dynamic knowledge graphs - Our transformation pipeline - Experiments with fine-tuned small-language models - Implementation details: - Inserting nodes and edges while preventing ambiguity through similarity matching - Tracking information origin across sources - Safely deleting documents from the graph without breaking relationships - Graph inference strategies

By the end of this talk, you'll understand why real-world knowledge graphs should be dynamic, how to build one yourself as well as the limitations and future directions of our approach.