Ontology Success Stories in Major Companies

Netflix

Netflix uses a richly structured internal video ontology to tag content by genre, mood, cast, plot devices, and more—powering its famous recommendation system. This ontology, structured as a directed acyclic graph (DAG), supports the creation of "micro-genres" and personalized recommendations based on subtle content signals. The result is a recommendation engine that increases viewer engagement and retention across millions of users.
Source

Google

Google's Knowledge Graph, launched in 2012, introduced structured ontological modeling into mainstream search. By connecting 500+ million entities and their relationships, the Knowledge Graph allows Google to provide direct answers and rich semantic context, replacing keyword-based search with concept-aware interaction. It underpins features like info boxes, "People Also Ask," and voice search.
Source

Apple (Siri)

Siri's natural language processing is grounded in ontology-driven knowledge graphs that map concepts like locations, contacts, restaurants, and events. This structure enables Siri to answer complex, contextual questions with precision. Originally developed by Siri's founders using Semantic Web technologies, this ontological approach remains a cornerstone of Apple's voice assistant system.
Source

Amazon (Alexa)

Amazon's Alexa uses a large-scale knowledge graph architecture, inherited and expanded from its acquisition of Evi (formerly True Knowledge). This ontology-based system models facts and relationships across thousands of categories, enabling Alexa to answer natural-language questions with contextual understanding. As reported in Wired, this technology allows Alexa to function not just as a voice interface, but as a semantic reasoner.
Source

Pinterest

Pinterest created a formal OWL ontology—called the Pinterest Taxonomy—to organize billions of pins and concepts into a structured "Taste Graph." Developed using WebProtégé and deployed in under two months, this ontology enables intelligent content discovery, advertising, and recommendations. The semantic model improved ad targeting accuracy and click-through rates significantly.
Source

Microsoft

Microsoft uses ontology-like knowledge graphs in products like Microsoft Graph and Azure’s GraphRAG (Graph Retrieval-Augmented Generation). GraphRAG, in particular, builds structured semantic models from enterprise documents to improve large language model (LLM) question answering. Microsoft reports a >55% improvement in factual grounding and a 40% gain in answer accuracy over standard retrieval.
Source