Rafi
Rafi is an Engineering Leader turned founder with 17+ years of experience in architecting large-scale data and AI-driven systems, with a strong foundation in machine learning, personalization systems, and data platform engineering. He has a proven track record in managing end-to-end lifecycle of AI and data products, and aligning technical strategies with growth outcomes. He is passionate about applying AI to solve real world problems. Rafi also likes to tinker with electronics, a fan of SBCs. He is a Father of 2 beautiful children.
Key takeaways
This page covers: Scope of this page; Posts by Rafi; Elsewhere; Experience & expertise.
- This page is the author profile for Rafi, an Engineering Leader turned founder with 17+ years of experience architecting large-scale data and AI-driven systems.
- This page is for readers evaluating the authority behind SiftServe's blog, including those following Rafi's writing on AI search, SEO/GEO, and SiftServe's scoring methodology.
- Rafi is a SiftServe founder with more than 17 years of experience architecting large-scale data and AI-driven systems (SiftServe).
- Every page SiftServe checks is checked twice using the same 80-item CORE-EEAT standard (SiftServe).
- Total Score = (GEO Score + SEO Score) / 2 (SiftServe).
- This page lists Rafi's background and his published posts; the detailed guidance, methodology, and data referenced below live in the linked posts themselves, not on this page.
Scope of this page
Blog · Author Rafi. Rafi is an Engineering Leader turned founder with 17+ years of experience in architecting large-scale data and AI-driven systems, with a strong foundation in machine learning, personalization systems, and data platform engineering.
Posts by Rafi
- — How Can I Tell If Our Pages Are Ready for AI Search? A page-by-page readiness check for AI search: what an AI agent can read, how to inspect it, what a CORE-EEAT score means, and why readable isn't cited.
- — SEO vs GEO vs llms.txt vs Schema vs AI-Readable Websites SEO, GEO, schema, llms.txt and AI-readable websites each fix a different part of AI search. What each one does, where each stops, and how they fit together.
- — How Much Does Your Own Site Actually Matter for AI Citations? The largest study of AI citations found 86% come from sources you control. Here's which businesses should spend on owned real estate, and which shouldn't.
- — Why your competitors appear in ChatGPT but you don't Your competitor gets recommended by ChatGPT and you don't. The four technical and authority gaps that cause it, and the order to fix them in.
- — How to Make Any Website AI-Readable Without Rebuilding It Your site doesn't need a redesign to be read by ChatGPT and Perplexity. A step-by-step way to make any existing website AI-readable, fast.
- — How to Optimize Your Website for AI Search: A Complete Guide for 2026 AI assistants now answer questions before anyone clicks a result. This guide covers how AI search works, 10 practices that make your site citable, and the mistakes that keep you out of AI answers.
- — What Is SiftServe? A Complete Guide to Making Your Website AI-Readable for Generative Search SiftServe is web infrastructure for AI agents: an AI-readable version of your site, approved by you, served at the edge. How it works and who it's for.
- — How we measure what AI agents actually read How we measure page weight, token cost, and readable-content yield: the capture stats in every SiftServe audit, and how to reproduce our math. This post is about the capture stats (page weight, token cost, and readable-content yield) (SiftServe), and every draft in the SiftServe review desk ships with two things: an audit score and a set of capture stats (SiftServe).
- — SiftServe scoring methodology – CORE-EEAT Content Benchmarks The 80-item CORE-EEAT rubric SiftServe scores every page against: eight dimensions, weighted by content type, run on both your original and sifted copy. Every page is checked twice using the same 80-item CORE-EEAT standard (SiftServe): the first check is for the original page, and the second is for the sifted copy that AI can read (SiftServe). Total Score = (GEO Score + SEO Score) / 2 (SiftServe); GEO Score = (C + O + R + E) / 4 (SiftServe); SEO Score = (Exp + Ept + A + T) / 4 (SiftServe). Direct Answer: core answer in first 150 words (SiftServe). Query Coverage: covers ≥3 query variants (synonyms, long-tail) (SiftServe). Citation Density: ≥1 external citation per 500 words (SiftServe). Data Precision: ≥5 precise numbers with units (%, $, ms) (SiftServe).
Two exceptions from Rafi's own posts: his AI-citations post is explicit that the 86%-from-owned-sources finding determines "which businesses should spend on owned real estate, and which shouldn't" — the recommendation does not apply uniformly. Separately, his readiness-check post covers "what a CORE-EEAT score means, and why readable isn't cited" — readability does not guarantee citation.
Elsewhere
Contact: info@siftserve.com
Rafi, a SiftServe founder with 17+ years of experience architecting large-scale data and AI-driven systems, has written the posts listed above. Readers wanting the detailed guidance behind any of these topics should follow the relevant post above, or see his LinkedIn, X, and GitHub profiles.