SaaS Metrics
Knowledge Graph AI Foundation
Semantic Web
AI Synthesis & Market Narrative
Semantic models and knowledge graphs are emerging as critical foundational layers for enterprise AI agents, enabling trusted knowledge grounding and balancing deterministic logic with LLMs. Database systems are evolving to support native graph queries, signaling a convergence of data paradigms for AI-driven applications.
Correlated Linguistic Patterns
["Architecting the Data Layer for AI Agents"
"Semantic Models"
"Graphwise to Help Enterprises Ground AI in Trusted Knowledge"
"Graph AI provider"
"Postgres 19 adds SQL\/PGQ graph queries"
"LLM-powered AI Agents and the Semantic Web Symbiosis"]
Driving Media Context
Presentation: Architecting the Data Layer for AI Agents: From Transactional Systems to MCP and Semantic Models
Fabiane Nardon shares how TOTVS prepares enterprise data for token-hungry AI agents. She discusses balancing deterministic logic and non-deterministic LLMs a...
Dereferencing URLs in RDF
Oakley Capital Invests in Graphwise to Help Enterprises Ground AI in Trusted Knowledge
The investment will accelerate the growth of the leading provider of AI knowledge platforms as companies seek to scale up AI cost-effectively NEW YORK, Aug. ...
Alexander Ioffe: How Fast Are Postgres 19 Graph Queries? Part 1: What Are They Actually Doing?
Postgres 19 adds SQL/PGQ graph queries. Measured against a PostgreSQL 19beta1 build, the fixed-depth graph query compiles to the exact same plan as a hand-wr...