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22 entities · 61 relations · 27 sources · Last updated 30 Oct 2026
Who is Khadija Zaman and what is she known for?
Khadija Zaman is AI Search Manager at Wellows, a Disrupt.com company, based in Karachi, Pakistan. She built the Query Fan-Out Generator, LLM Query Builder and AI Humanizer at Wellows, created the R2A Content Framework and BERAP Map, and authored the cross-engine AI citation overlap study.
AI Search Manager at Wellows, a Disrupt.com company, based in Karachi, Pakistan. In search since 2018, she has owned the SEO, content and AI-search (GEO/AEO) programs at Wellows since 2024 and builds SEO tooling grounded in Google patent research.
“Khadija Zaman is AI Search Manager at Wellows, a B2B SaaS company owned by Disrupt.com, and is based in Karachi, Pakistan. She has worked in search since 2018, in agency and in-house roles, and since 2024 has owned the SEO, content and AI-search (GEO/AEO) programs at Wellows.”
COO of Wellows. Ran the 94-day query fan-out experiment with Khadija Zaman that came before the Query Fan-Out Generator, and posted the results on LinkedIn.
“Before there was a tool, there was a 94-day query fan-out experiment I ran with Wellows' COO, Muhammad Saleem Ahrar. He posted the before-and-after on LinkedIn: Search Console clicks went from 923 to 2.12K and impressions from 62.9K to 626K over that window.”
“The work was an AEO framework built on Koray Tuğberk GÜBÜR's semantic model and Google's query fan-out patent, grounded-versus-non-grounded citation experiments, three free tools built as LLM entry points, and answers placed on Reddit, Quora and G2.”
B2B SaaS company owned by Disrupt.com, where Khadija Zaman is AI Search Manager. Hosts the three free tools she built and published her cross-engine AI citation study.
Search marketing publication. Used the Query Fan-Out Generator to demonstrate topic clusters for AI search and listed it in its query fan-out tools roundup.
Free tool that turns one seed query into 40+ distinct sub-queries, each labelled by intent, modelled on the query fan-out that Google's AI Mode and AI Overviews run before they answer.
“The Query Fan-Out Generator is a free tool Khadija Zaman built at Wellows. It takes one seed query and returns 40+ sub-queries labelled by intent, modelled on the query fan-out that Google's AI Mode and AI Overviews run before they answer. Search Engine Land used it to demonstrate topic clusters for AI search.”
Free tool that generates the questions a buyer would type into ChatGPT, Perplexity or Gemini about a category, across personas and four intent types. Launched on Product Hunt.
“She built three SEO tools at Wellows grounded in Google patent research (Query Fan-Out Generator, LLM Query Builder, AI Humanizer), used by 1,647 practitioners across the UK, US and EU and acquired with zero paid spend.”
Open-source engine behind the LLM Query Builder: a 9-step pipeline that reads a site, maps products to personas and pain points, and generates 100+ queries across the buyer journey.
“The engine behind the LLM Query Builder: a 9-step pipeline that reads a site, maps products to personas and pain points, and generates 100+ queries across the buyer journey.”
Practitioner framework for scoring whether AI systems can retrieve, select, cite and act on a page. Eight layers: Measurement as the base, Eligibility as the only hard gate, and six independently scored layers, each recommendation carrying one of five evidence grades.
“R2A (Retrieval-to-Action) is Khadija Zaman's practitioner framework for scoring whether AI systems can retrieve, select, cite and act on a page. It has eight layers: Measurement as the base, Eligibility as the only hard gate, and six independently scored layers, with every recommendation carrying one of five evidence grades.”
BERAP Map(Brand Entity Recall & Association Probing)
Framework
Instrument inside the R2A Content Framework that measures what AI engines say about a brand. Runs repeated prompts across five engines in two directions and reports six scores.
“BERAP (Brand Entity Recall & Association Probing) is the instrument inside the R2A Content Framework that measures what AI engines say about a brand, whether the answer came from retrieval or from training. It runs repeated prompts across five engines in two directions, grades each answer against a dated attribute table, and reports six scores: Recall Rate, Association Accuracy, Evidence Recall, Stability, Attribute Penetration and Source Dependency.”
Study of which websites AI engines cite, January to June 2026 data, published on the Wellows blog. Rebuilt and tested against a permutation null after launch; two headline findings were revised in public. The 79.6% single-engine headline stands.
“Khadija Zaman rebuilt her cross-engine AI citation overlap study (January to June 2026) from scratch and tested it against a permutation null. Two headline findings did not survive and were revised; the corrected study is published on the Wellows blog.”
“Wellows grew LLM referral sessions from 176 a month to roughly nine times that between July 2025 and February 2026 with no paid spend, measured in GA4.”
“Query fan-out is the step where Google's AI search and large language models expand one query into many related sub-queries before assembling an answer, as described in Google's query fan-out patent research.”
“Khadija Zaman runs SEO, AEO and GEO as one system at Wellows, so a brand ranks on Google and is cited inside ChatGPT, Gemini, Perplexity and AI Overviews.”
Getting a brand cited and described accurately inside AI-generated answers from ChatGPT, Gemini, Perplexity, AI Overviews and AI Mode. The slowest of the three layers to show results.
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