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Projects

Things I've built to see how search and AI engines actually behave. Some have real users. Some are open code you can run yourself.

  • 1,647practitioners used three tools I built at Wellows
  • 829of them on the Query Fan-Out Generator
  • 7public GitHub repos listed on this page
  • 2Search Engine Land guides that use or list the Query Fan-Out Generator

Sources: GA4 (9 Sep 2026), github.com/KhadijaZaman (7 Oct 2026), searchengineland.com (7 Oct 2026). User counts are from my own tracking window, not lifetime totals.

Tools I built at Wellows 3

Built in-house at Wellows as free entry points for practitioners. Wellows hosts them; the build and the measurement were mine.

Live

LLM Query Builder

Generates the questions a buyer would actually type into ChatGPT, Perplexity or Gemini about your category, across personas and four intent types.

  • 149users (GA4, as of 9 Sep 2026)
  • Launched on Product Hunt (Masab Gadit's launch post)
Live

AI Humanizer

Rewrites AI drafts so they read naturally without losing topical depth, with before-and-after stats.

  • 669users (GA4, as of 9 Sep 2026)
  • 60 to 72%GA4 engagement rate across the months I tracked (GA4)

Open source on GitHub 5

Public code on github.com/KhadijaZaman. Several of these are the engines behind the tools above.

Open source · TypeScript · Node · OpenAI

LLM AI Search Query Builder

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.

Open source · TypeScript · Postgres · Common Crawl

Domain Authority Explorer

An open-data alternative to proprietary authority scores, built on the Common Crawl Web Graph of about 121 million domains, with monthly history back to January 2018.

Open source · TypeScript · React · Express

Citation Auditor

Scrapes a set of pages, scores each for the signals AI answer engines cite, and exports a spreadsheet a content team can work through.

Open source · TypeScript · MCP · OAuth 2.0 · MIT

Wellows MCP Server

An MCP server that lets Claude or any MCP client check a domain's citation score in Google AI Overviews without opening a dashboard.

Frameworks 2

Methods I use to score and test pages for AI search, written up in full.

Published

R2A Content Framework

Scores whether AI systems can retrieve, select, cite and act on a page: eight layers, one hard gate, and a graded evidence level on every recommendation.

Published

BERAP Map

Probes five AI engines with repeated prompts and grades answers against a dated attribute table, producing six scores for what models remember about a brand.

Free tools on this site 4

Small, no-sign-up tools that run in your browser.

  • AEO Citeability Checker

    Scores how ready your content is to be cited by AI answer engines, with fixes.

    Try it →
  • SERP Snippet Preview

    Approximate pixel-width preview of a title and meta description, with truncation warnings.

    Try it →
  • Query Fan-Out Explorer

    Expands a seed query into 44 template sub-queries grouped by fan-out type.

    Try it →
  • Schema JSON-LD Generator

    Fill a short form, copy ready-to-paste Article, FAQ or Person structured data.

    Try it →

Where it started 2

Early builds from when I was learning how retrieval works.

  • Custom Semantic Search Engine Python · Word2Vec · BART

    Semantic document search from scratch: embeddings, cosine-similarity ranking and summarisation, in a Colab notebook.

    GitHub →
  • LLM Semantic SEO Evaluation Tool Python · Streamlit · Jupyter

    Scrapes a URL and scores its content on semantic SEO criteria such as context coverage, entities and internal linking.

    GitHub →
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