Product

One loop, from what AI says about you to what changed.

The AI Growth OS is a loop rather than a dashboard. Each part feeds the next: the questions produce answers, the answers produce reasons, the reasons produce one action at a time, and publishing the work sends the questions back round.

Quick answer

ModernTechLap is an AI growth platform. It asks the buyer questions in your category across seven AI systems, records whether you were mentioned, recommended and cited, explains why competitors win, turns each gap into one scored action a person approves, and re-asks those questions after you publish.

The four parts of the loop

Each one is a page of its own. They share the same stored answers, which is why an action can name the questions it is meant to move.

How one question becomes a change you can see

Six steps, in this order, for every question in your set.

  1. Ask the questions your buyers ask

    The product builds a question set from what you sell and who you sell it to, then asks it across the AI systems you have connected. You can edit the set before it runs.

  2. Read every answer the same way

    Mentioned or not. Recommended or not, and in what position. Which sources the answer leaned on. Which other companies were named. Stored per answer, per engine, so a change has something to be compared against.

  3. Explain the losses

    For the questions you lose, the product shows who won them, the sources behind those wins, and the claims those companies are associated with that you are not.

  4. Turn each gap into one action

    Not a score. One action, scored on impact, confidence, effort and urgency, with the questions it is meant to move. A person approves it, postpones it or rejects it.

  5. Draft it, review it, publish it

    Agents prepare drafts from the stored evidence. Every draft goes through review by a person before it goes anywhere, and the workspace keeps the versions.

  6. Ask again and compare

    Publishing an asset marks its action done and re-asks that action's questions about a week later, so the before and after sit next to each other instead of in two different reports.

The AI systems we ask

We write for engines in general rather than for three of them. Which ones matter in your category is an empirical question, and the product answers it by asking all of them.

  • ChatGPT
  • Claude
  • Gemini
  • Perplexity
  • Grok
  • Google AI Overviews
  • Microsoft Copilot

Engines are not limited by plan. Every plan asks every engine you have connected, so a cheaper plan never means a narrower view of the market.

What you actually get

The parts you can hand to someone else, or leave running.

  • Reports you can hand over: CSV export for the raw rows, print to PDF for the version that goes in a deck.
  • An optional GA4 connection, so AI-referred sessions and revenue sit beside the visibility numbers instead of in another tab.
  • Scheduled refresh, monthly, weekly or daily depending on your plan, so the questions are re-asked without anyone remembering to do it.
  • A free baseline that starts by itself when you sign up, with the top three actions visible read only.
  • An AI Readiness audit of your site: robots.txt, llms.txt, sitemap, structured data and whether your pages answer the question they target.

What this is not

Worth saying plainly, because the category is full of the opposite.

  • Not a keyword rank tracker. The unit here is a buyer question and the answer it produced, not a position in a list of links.
  • Not autonomous publishing. Agents draft. Nothing external happens without a person approving it first.
  • Not a guarantee of placement. Nobody outside the model vendors controls what a model says, and any vendor promising a citation is guessing.
  • Not a dashboard of scores. Every finding in the product exists to produce an action with a reason attached.

Planned, not available yet

These are on the roadmap and are not part of the product today. They are listed so nothing above reads as more than it is.

  • Modelling where in a purchase a question sits, with personas walking it, is planned. Today questions are grouped by intent, which is the evidence that modelling would run on.
  • Ranking actions from your own past results is planned. Scoring today weighs the evidence behind an action, and is not trained on your history.
  • Publishing straight from the product, to this publication or into your own CMS, is planned. Drafts leave the workspace as content you paste or export, and articles are submitted through the publishing side of the site.
  • Multiple named users, each with their own permissions, is planned. An account is one workspace today, so an approval is recorded against the account rather than against a person.

What these results are, and are not

Everything the product reports is a snapshot of the questions and engines that were tested, on the day they ran. AI answers change between runs, accounts and regions, so results vary and nothing here is a ranking. We do not guarantee that any engine will mention, recommend, cite or include you.

ModernTechLap measures and influences the evidence around a business; it does not control AI model outputs.

Common questions

Which AI systems does ModernTechLap track?
ChatGPT, Claude, Gemini, Perplexity, Grok, Google AI Overviews and Microsoft Copilot, for the systems you connect. Engines are not limited by plan, so a cheaper plan asks the same engines as an expensive one.
Do I need to pay to see anything?
No. A free baseline starts by itself when you sign up and needs no card. It shows your visibility for the questions it tested and the top three actions, read only.
Can you guarantee an AI will recommend us?
No, and nobody can. Results are snapshots of the questions and engines that were tested on the day they ran, and the same question can return a different answer tomorrow. ModernTechLap measures and influences the evidence around a business; it does not control AI model outputs.
Will the product publish or send anything on its own?
No. The five agents draft only. Content, entity fixes and outreach messages all wait in review until a person approves them, and the workspace records the version that was approved.

Find out what AI says about you. Then change it.

Free baseline, 25 buyer questions, every AI system you connect. About ten minutes, no card.

Run your free baseline

25 buyer questions across the AI systems you connect, for .

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