Find out what it takes to be recommended in AI Search

Kelsey reverse engineers why AI recommends your competitors, finds the content gaps, and measures which changes improve your results.

Multiple probes per prompt · Every finding linked to evidence · Every change measured for 30 days

Kelsey Results analytics showing AI search performance, experiments, and visibility impact

Try asking Kelsey

Did the refresh work?
Kelsey Just now

The Salesforce comparison refresh is working. Recommendation rate increased from 20% to 70%.

Northstar vs. Salesforce refresh

Experiment running

Published 18 days ago · 8 prompts tracked

Published change

  • Added implementation timeline
  • Added migration comparison
  • Added reporting capabilities

Review change →

Performance during experiment

Up from 20% before publication.

Kelsey

Reading your tracked data…
Kelsey Just now

Review change →

Ask anything about your brand...

Turn AI answers into changes you can test.

A single ChatGPT answer cannot tell you whether your strategy is working. Answers vary, citations change, and brands sometimes appear by chance.

Kelsey analyzes repeated searches together to find the criteria, sources, and verifiable facts that consistently influence recommendations.

Other AI search tracking tools

Track hundreds of useless prompts

  • Track where your brand appears
  • Compare mentions with competitors
  • Review answers and cited sources
  • Leave your team to interpret the results

Kelsey

Shows you what to change

  • Find the patterns behind recommendations
  • See which evidence your website is missing
  • Prepare a specific change worth testing
  • Measure whether that change improved the result

Customer story

“I’ve been using Kelsey to improve GEO rankings at Alertly and get a better understanding of how ChatGPT and other AI engines are suggesting the product. Kelsey makes AI less of a black box and clearly shows which prompts you’re showing up for, but the real benefit is being guided with actionable to-dos to improve your visibility.”
Kyle Gawley Kyle Alertly

• How it works

The tool that reverse engineers AI recommendations

Kelsey finds where competitors are influencing AI answers, prepares the changes most likely to improve your position, and runs an experiment to measure what happens after you publish

01 Understand

Measure the answers that matter

Measure repeated answers and find where competitors consistently win.

Answer frequency

Answer A
Answer B
Answer C
Answer D
Answer E

8 buying questions · 24 answers reviewed

02 Prepare

Turn evidence into verified work

Kelsey investigates the criteria, verifies important facts, and prepares the change.

  • Criteria identified
  • Evidence gathered
  • Facts verified
  • Change prepared

4 criteria found · 2 site gaps

03 Measure

See whether the change worked

Measure the questions the change was designed to influence.

Answer frequency over time

30-day experiment · Early positive result

Meet Kelsey, the AI search agent that gets you mentioned

Kelsey analyzes AI search data and gives you clear, actionable answers—from what to track, to where you’re losing, to what to do next.

Explore Kelsey agent

Agencies

Scale AI Search delivery without scaling your team

Kelsey turns your agency’s AI Search strategy into a repeatable system that finds the highest-impact opportunities, prepares the work, routes it for review, and shows clients what changed.

  • Win clients with a real plan Run a prospect analysis that shows where competitors are winning, what is influencing the answers, and the work you would prioritize first.
  • Turn your process into repeatable delivery Use the same proven playbook across every account while grounding each recommendation, brief, and content update in that client’s prompts, sources, competitors, and brand.
  • Move from recommendation to review Prepare comparison pages, content refreshes, new sections, briefs, and authority-building opportunities without rebuilding the research or starting from a blank document.
  • Prove what the work changed Connect completed work back to the prompts and sources that triggered it, then show clients how their mentions, citations, and competitive position changed over time.
Kelsey monthly AI search brief showing client reporting for agencies

FAQ

Frequently asked questions

Get clear answers about how Kelsey finds recommendation criteria, prepares evidence-backed changes, and measures what improves after you publish.

Need more help? View all FAQsContact our team

Kelsey is an AI Search recommendation platform. It tracks the buying questions that matter to your brand, uncovers the criteria influencing AI recommendations, prepares evidence-backed website changes, and measures what happens after you publish.

Kelsey analyzes repeated answers for the same buyer intent, identifies recurring recommendation criteria, reviews the sources influencing those answers, and compares the winning brands against your website. Every finding links back to the supporting answers, sources, and pages.

Kelsey strengthens the evidence by collecting repeated baselines, defining target prompts, monitoring comparison prompts, recording exactly what changed, and measuring results for 30 days.

Kelsey currently tracks ChatGPT, Perplexity, and Gemini, the platforms driving the most real usage today.

Yes. Agencies can track multiple client brands from one workspace, and B2B marketing teams can monitor competitors, product lines, and prompt coverage over time. Agency plans also include shareable dashboards and exports for client reporting.

SEO tools track rankings on Google. Kelsey tracks recommendations inside AI answers. AI does not show pages. It recommends a small set of options, and Kelsey shows whether you are one of them.

Free AI visibility report

Build the brand AI recommends

Kelsey tracks the buying prompts your customers ask across ChatGPT, Perplexity, and Gemini, then shows where your brand appears, which competitors win, and what to improve next.

Monitoring answers across

ChatGPT Gemini Perplexity
Kelsey analytics showing AI search performance over time and experiment results