01
AI Agents
Ontology vs. RAG: Which Agent Questions Each One Can Answer
Compare ontology vs. RAG by question type, see where vector similarity fails, and learn how ontology-grounded retrieval combines both in one pipeline.
Contributing author
Karthik Pasupathy
Contributing Writer — AI Context & Agents
Karthik Pasupathy is a product marketer and the founder of Rampkit, with over a decade spent helping B2B SaaS and AI-infrastructure companies explain complex products to enterprise buyers and practitioners. He has led marketing for early-stage companies across FinTech, CCaaS, and mortgage technology. At Atlan, he writes on AI context, agentic systems, and RAG metadata.
/ Profile
About Karthik.
Karthik Pasupathy is a technical writer turned product marketer and founder of Rampkit, where he helps technical B2B SaaS and AI infrastructure companies explain complex products to the people they are built for. His work sits at the intersection of content, product understanding, and market education — turning dense technical ideas into clear narratives for enterprise buyers, practitioners, and technical decision-makers.
Over the last decade, Karthik has worked with SaaS companies across AI infrastructure, DevOps, APIs, FinTech, CCaaS, mortgage technology, and enterprise software. His writing focuses on helping teams communicate why their product matters, how it fits into a larger technical workflow, and what problems it solves for specific user personas.
His current work explores AI context, agentic systems, RAG metadata, and how enterprises can make AI outputs more relevant, grounded, and useful. He brings a content-first lens to technical topics without stripping away the nuance that makes them valuable.
Press, talks & code
Recent articles by Karthik Pasupathy.
12 showing
- 02Data & AI
Build vs Buy a Semantic Layer: Real Costs and How to Decide
Build vs buy semantic layer: compare six ownership models, the cost drivers behind each, published pricing, and what AI agents need beyond metrics.
- 03AI Agents
Is the Semantic Layer Dead? Where Business Meaning Lives Now
Is the semantic layer dead? One layer for every tool never became the default, but AI put business definitions in the query path. See the…
- 04Data & AI
Semantic Layer vs. Business Glossary: What Each Holds
Semantic layer vs business glossary: a glossary records what a metric means and who approved it, a semantic layer computes it. See how to link…
- 05Semantic Layer
Semantic Layer vs. Knowledge Graph: What Each Gives AI Agents
Semantic layer vs knowledge graph: compare how each models meaning, what the LLM benchmarks show, and when AI agents need governed metrics and graph paths.
- 06Ontology
What Is Entity Resolution and Why Does It Matter for Ontologies?
Learn what entity resolution is, how matching works, and why owl:sameAs, survivorship, and provenance decide what an ontology tells your AI agents.
- 07AI Agents
Agentic Software Factory: Specs, Agents, and Enterprise Context
Learn how an agentic software factory works, where humans approve, and why data products need business context alongside specifications and code.
- 08Google Cloud and the Context Layer
Google Agentic Data Cloud vs Context Layer: Who Owns the Meaning?
Compare Google Agentic Data Cloud with a neutral context layer: current feature status, business meaning, agent access, portability, and coexistence.
- 09Ontology
How Do AI Agents Use an Ontology? One Request Traced Step by Step
Trace how AI agents use an ontology at runtime to resolve terms, plan queries, apply policy context, coordinate handoffs, and explain each answer.
- 10AI Agents
Why a Neutral Ontology Layer Matters: Own Your Business Meaning
Learn why a neutral ontology layer keeps business meaning owned, portable, and consistent across every AI agent, model, and platform you run.
- 11AI Agents
Why AI Grounding Is Driving Ontology Demand for Enterprise Agents
Learn why AI grounding put ontologies back on the enterprise roadmap, what ungrounded agents get wrong, and why a first ontology draft is now cheaper…
- 12AI Agents
Ontology and Context Layer: How They Fit in Your AI Architecture
See where the ontology sits inside a context layer and how binding, approval, versioning, and delivery keep enterprise meaning current for AI.
Transparency
Editorial relationship
Freelance contributor agreement
Karthik contributes to Atlan as an independent consultant under a freelance content agreement. He reviews and approves every article published under his byline before publication. Atlan does not pay for placement of any external coverage.
Reach Karthik