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AI Readiness
How to Evaluate an AI Readiness Platform in 2026
Evaluate an AI readiness platform by testing context, certification, runtime delivery, traceability, and portability, not a one-time readiness score.
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
- 02AI Agents
RAG Pipeline vs. Context Layer: What Custom Retrieval Costs
See how RAG pipeline vs. context layer total cost of ownership breaks down across engineering, maintenance, permissions, evaluation, and scale for AI teams.
- 03AI Agents
ROI of AI Agent Governance: Governed vs. Ungoverned Access
Calculate the ROI of AI agent governance: faster deployment, less review and rework, reusable context, and lower failure exposure from governed access.
- 04Semantic Layer
Context Engineering vs. Semantic Layer: What Each Does
Context engineering vs. semantic layer: compare what each one actually does, how they work together, and what your AI agents need first to run well.
- 05AI Agent Operations
Agentic Workflows vs. RPA: Why Agents Need a Context Layer
Compare agentic workflows vs. RPA by mechanics, failure modes, context requirements, and migration choices for enterprise automation teams in 2026.
- 06Multi-Agent Context Management
Context Management for Multi-Agent Systems: Context Patterns
Learn how to manage shared context across multi-agent systems using governed context stores, scoped sub-agents, conflict rules, and refresh cycles.
- 07AI Governance
OpenAI Frontier vs. Independent AI Governance Platform
See how OpenAI Frontier compares with an independent AI governance layer on policy ownership, model coverage, audit portability, and integration cost.
- 08AI Agent Memory
How AI Agents Read and Write Memory: The Mechanics
How do AI agents read and write memory? Learn the mechanics behind short-term, long-term, episodic, and semantic memory, and why context matters.
- 09Agent Protocols
Code Mode vs Function Calling: Benchmarks and When to Use Each
Compare code mode vs. function calling benchmarks, tradeoffs, security needs, and the workflow patterns where each approach works best in production agents.
- 10Knowledge Graphs for AI Agents
Active vs. Static Knowledge Graph: What's the Difference?
Compare active and static knowledge graphs for AI agents. See why freshness architecture affects hallucination rates and how to evaluate mutability.
- 11AI Agents
What Are the Pitfalls of Building an Enterprise Knowledge Graph?
Enterprise knowledge graph projects fail across three fronts: organizational, technical, and economic. See the named failure patterns and how to avoid them.
- 12AI Agent Protocols
MCP vs OpenAI Function Calling Design Philosophy
Compare MCP and OpenAI function calling through interface control, foundation stewardship, portability, and the context enterprises need behind both.
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