Popular reads
The Unconscious Patient Problem: A Look at the Importance of Entity Resolution in Healthcare and Life Sciences
The Databricks DI Platform, built on lakehouse architecture, coupled with Stardog as a semantic layer, provides a robust and scalable alternative to tedious and brittle traditional approaches to matching patient records.
How AI Uses Stardog
In our previous post we answered the question how Stardog uses AI by explaining our use of Hybrid AI with LLM to build, manage, and query knowledge graphs with ordinary language. The question today goes the other way around; how does AI use Stardog, that is, how does enterprise generative AI use an enterprise knowledge graph?
Designing LLM Applications with Knowledge Graphs and LangChain
Voicebox, our LLM-powered knowledge engineer, accelerates time to value by making it easier to build and query knowledge graphs, but we haven’t yet said much about how it works. In this blog I will explain the high-level design of Voicebox, including how we use LangChain.
Latest posts
The AI Chessboard: Why Every Great AI System Needs a Semantic Layer
LLMs, agents, and retrieval are only pieces. Stardog’s CTO explains why a governed semantic layer for AI is what makes them play as one coherent system.
Hundreds of AI Conversations. One Clear Pattern.
Real AI value starts with trusted data. Stardog CEO, Craig Harper, explains 4 principles for enterprise semantics, from open standards to RDF knowledge graphs.
GenAI Cost Problems Are Not Model Problems
GenAI costs are driven by token volume, not model pricing alone. Learn how semantic layers reduce the token bloat caused by retrieval augmented generation (RAG) and Text-to-SQL patterns.
The AI Race Won't Be Won by AI Marketing Slop
In a noisy AI landscape, Stardog’s EVP of Marketing, Sandy Terry, makes the case for why trust can’t be automated and what that means for enterprise AI.
The Semantic Control Plane: Building Trust in Enterprise AI
The hardest problem in Enterprise AI isn’t reasoning — it’s trust. Stardog CPO, Navin Sharma, on the Semantic Control Plane: where humans and agents build confidence before agents act.
Why the Next Era of Enterprise AI is About Scaling Human and Artificial Intelligence Together
The future of enterprise AI isn’t about smarter models — it’s about scaling human and AI intelligence together. Stardog CPO, Navin Sharma, on what comes next.
AI and Your Data Speak Different Languages
The biggest obstacle to enterprise AI isn’t the model — it’s the data. Craig Harper, CEO of Stardog, on why the next chapter of AI is about knowledge.
25 Years in Semantics: Building the Cognitive Backbone of the Enterprise
Stardog CTO Evren Sirin on 25 years in semantic technology: why the meaning gap persists and what a cognitive backbone for enterprise AI requires.
What LLMs Don’t Know
Your enterprise AI agents are failing. Not because they can’t think, but because they can’t access what matters most.
Foundation Models Know Enough
There’s a truth that traditional ontology communities are reluctant to face: Large language models already contain world models. They’re not formally axiomatized. They’re not neat. They’re not hand-built by committees. But they work.
Taming the Risk Hydra: Stardog and the Future of BCBS-239 Compliance
BCBS-239, issued by the Basel Committee on Banking Supervision, establishes principles for effective risk data aggregation and risk reporting (RDARR).
Tariff Chaos is a C-Suite Problem
Stardog’s Knowledge Graph-powered semantic layer gives the C-suite real-time, AI-powered visibility into supply chain exposure.