Free sample

Try CitePack free on one question

See what AI engines tell your buyers when they ask one buying question.

  • One buying question. Pick one of three for your category, or write your own.
  • Two of the four AI engines, your pick, each asked three times.
  • Who is named first in each answer, and whether your company appears and where.
  • The other companies named, and the sources the engines cited.

One free sample per company. We email you the link. It covers one question on two of the four engines. A full Decision Map covers five questions on all four engines, with a Work Plan.

See the full Decision Map
CitePack vs LensCore

CitePack and LensCore: what each one is built to show.

LensCore is built to score how AI engines discover a business, as one number out of 100. CitePack is built to show how each engine chose who to put forward in your buying decision: 60 observations of that decision, framed from your buyers’ real buying situations, asked three times on each of four engines, with every answer kept and the work ranked.
On this page

How CitePack reaches 60 observations of one decision.

CitePack maps how AI engines choose in a defined buying decision: one offering, the buying category it’s bought in, and the market its buyers are in. The category and the buyer’s situation shape which companies an engine puts forward, so the decision is defined before anything is asked.

CitePack frames the questions. Each is drafted for your offering, its buying category and your buyers’ market, one for every real buying situation across the whole decision: a buyer just starting to look, one with a job to get done, one with a condition they won’t bend on, one weighing what matters most, and one moving away from what they use now. Each carries the buyer specifics that matter, like the work to be done, a must-have or what they use today. None of it is a fixed prompt from a library. You read every question, change any wording you like and approve all five. The final go is yours. Then every engine gets them exactly as written.

  1. 5buying situations, framed by CitePack
  2. × 4engines: ChatGPT, Claude, Gemini, Perplexity
  3. × 3clean repeats on each engine
  4. = 60observations of one decision, every answer kept

Each question goes to ChatGPT, Claude, Gemini and Perplexity, three times on each engine, and every repeat is clean. Five situations, four engines, three repeats: 60 observations of one defined decision. Every answer is kept word for word, with the searches the engine ran and the pages it read. So the pattern shows which names an engine keeps putting forward, which turn up once, and how each engine chose.

The Work Plan turns those answers into ranked work. Each item names the answers and pages behind it, who does it and what to check when you measure again.

Map each offering, category and market you sell into, and each map adds to the picture of where your company stands in its market.

The two methods.

What is comparedCitePackLensCore
Where the questions come fromFramed by CitePack for your offering, category and market: one per real buying situation across the whole decision, with the buyer specifics that matter. You give the final go.“10 core questions fixed per business type … and 15 adaptive questions generated from what your site actually sells and where”
How the pattern showsEach question three times on each of four engines, every repeat clean: 60 observations of one decision, every answer kept word for word.“Each question is asked once per engine, on the day of the scan.”
MarketYour buyers’ market, named in every question and set on every engine by default.“The 25 questions are generated for your category and market.”
The resultNo single score. Put forward, mentioned and cited are kept apart, and every finding opens to the answers behind it.“The LensCore Discovery Index combines five factors (presence, prominence, recommendation, citation, entity) into one number out of 100.”
What you act onA Work Plan ranked from the answers, each item tied to the answers and pages behind it.“paste-ready fixes”

Why each question is asked three times.

LensCore’s docs say of their own scan: “One pass per engine is a sample, not a census. Each of the 25 questions is asked once per engine. That is enough to see whether an engine reaches for you at all, and not enough to measure a stable percentage.” CitePack asks each question three times on each engine, so a map shows which names an engine keeps putting forward and which turn up once.

A number or a map.

LensCore rolls five factors into one number out of 100. CitePack keeps the facts apart: whether you were mentioned, whether you were put forward as an option, whether a page of yours was cited. Each count shows what it is out of and opens to the answers behind it.

Fixes or ranked work.

LensCore offers paste-ready fixes. The CitePack Work Plan ranks the work the answers point to. Each item names the question, the answers, a verbatim search or quote that shows it, an effort, an owner and a check.

Who each fits.

LensCore fits a team that wants one discovery number to watch. CitePack fits a team that wants to see how the engines choose in each decision it sells into, with every answer kept and the work ranked.

Sources.

Every sentence about LensCore on this page is quoted or summarised from these pages, read on 22 October 2026.

How AI chooses between vendors →Read the methodology →See what the Work Plan holds →See pricing →