Ka Ling Wu·2d agoOntology vs Knowledge Graph vs Semantic Layer, Shown on One Subscription BusinessThe same Customer, Subscription and Invoice built as a taxonomy, an ontology, a knowledge graph and a semantic layer, and what each…
Muhammad Awais·Nov 4Why Traditional RAG is Failing Your AI Strategy (and How GraphRAG Fixes It)Standard Retrieval-Augmented Generation (RAG) has become the default architecture for enterprise generative AI systems. On paper, the…
Navaneethan L·Nov 3Ontology Engineering for Enterprise AI: Grounding LLM Reasoning in Domain StructureThe previous article established that knowledge graphs are the right retrieval primitive for multi-hop, relationship-aware enterprise…A response icon1A response icon1
Navaneethan L·Nov 3Knowledge Graphs as AI Memory: When Vector Search Is Not EnoughVector search is the right retrieval primitive for most enterprise RAG systems. Embed a query, find the nearest chunks, assemble context…
Muhammad Awais·Oct 28Beyond Vector Search: 5 Surprising Insights on How GraphRAG and Agent Memory Are Reshaping AIIntroduction: The Hidden Ceiling of Modern AI Retrieval
Ram Sushen·Oct 22Making 101 Tools MCP-Native and Agent-Friendly — for True Plug-and-PlayA Working Journal — Part 5 of 7
Tuana Irkey (Tui)·Oct 16The Shape of the DisagreementA knowledge graph for contested evidence, and where better AI models actually help
Manoj Kumar Vohra·Oct 9Relevant Is Not the Same as Right: Can Retrieval Tell Which Source to Trust?Whether you retrieve from documents or from a knowledge graph, sources disagree. We gave look-alike evidence to ten scoring systems and…A response icon2A response icon2
Akhilesh Yadav·Oct 6Cross-encoders changed how I think about retrieval precisionHybrid retrieval gets the right candidates into the room. Cross-encoders figure out which one actually belongs at the table. Plus…
