DelveDeep
AI search analytics for brands and agencies

Understand how AI engines see your brand.

DelveDeep tracks visibility, citations, competitors and source quality across AI answers. Turn conversational search into measurable intelligence.

Which pages speak positively or negatively about your brand?
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ChatGPTGeminiPerplexityClaudeDeepSeek
Q2 brand audit
AI Visibility Score74.2
+12.8%
Mentions68%
Citations41
Competitors9
Model coverage
GPTHigh
GEMMedium
PRXWatch
Top cited sources
owned domain18
industry media11
public profiles8
Search is becoming conversational.

DelveDeep helps teams measure where they appear, why they are cited and which actions improve brand presence inside AI-generated answers.

Product

A practical control room for AI visibility.

DelveDeep brings AI answer analysis, source monitoring and technical domain audits into one workflow.

AI visibility analysis

See whether your brand appears in AI answers, how it is framed, where it ranks and which alternatives are mentioned.

Competitor benchmarking

Compare brands, competitors and peer sets to understand who is cited, recommended or ignored by AI engines.

Source and link analysis

Identify the sources that shape AI answers: cited domains, recurring pages, owned assets and third-party references.

Domain audit

Check whether your website is readable, structured and ready to be understood by crawlers and AI systems.

Broken link checks

Check whether the URLs cited by AI models are live, degraded or broken, and which ones should be recovered first.

Action plans

Turn findings into operational priorities: protect strong sources, refresh weak pages and mitigate reputation risks.

AI visibility radar

A fast view of presence, sentiment, citations and source strength.

Capabilities

From model answers to concrete actions.

The product goes beyond monitoring: it connects model answers to the sources that influence them and the technical signals that make them accessible.

Visibility

What AI says about you

DelveDeep measures brand presence, sentiment and positioning across answers from major AI models.

Sources

Which pages shape the answer

The platform shows which sources are cited, how often they appear and whether they are controlled by the brand.

Foundation

Whether your domain is AI-ready

The domain audit checks signals such as crawlability, robots.txt, sitemap, schema, canonical tags and content structure.

Question coverage

Compare how often AI systems answer with your brand in the frame.

Source action plan

Decide what to protect, recover, refresh or mitigate.

Protect

Positive and working sources should be monitored, preserved and kept up to date.

Recover

Broken or degraded links can be recovered before they reduce trust and citation quality.

Refresh

Cited but weak pages can be rewritten, enriched or made clearer for AI systems.

Mitigate

Negative or misleading sources should be tracked and countered with stronger signals.

Source mix

Separate owned assets, third-party reviews and risky sources.

Method

Repeatable analysis, not one-off screenshots.

DelveDeep combines prompt libraries, multi-engine runs, Lighthouse-style KPIs and evidence-based recommendations.

Prompt setsCategory, brand, local and comparison queries
ModelsMulti-engine panel across major AI answer systems
OutputsScores, citations, link checks and executive summaries
MonitoringCompare competitors, periods and report versions over time
ReportsOperational evidence and board-ready exports

AI engines are large language models: each answer is generated for a single user and never published as a ranked page, which is why visibility has to be sampled repeatedly instead of read off a results page.

Getting started

How to measure your brand's AI visibility

The same four steps every DelveDeep run follows, whether it is a one-off audit or a scheduled campaign.

  1. 1

    Define the questions that matter

    Start from the questions your buyers actually ask an AI engine: category, brand, comparison and local queries. DelveDeep builds the prompt set from a structured library rather than a handful of ad-hoc prompts.

  2. 2

    Run the panel of AI engines

    The same prompt set is sent to several engines in one run, so differences come from the models and not from the wording. Repeat on a schedule to get a comparable time series.

  3. 3

    Read mentions, sentiment and sources

    Each answer is analysed for brand mentions, sentiment, competitor position and the sources cited, then scored with Lighthouse-style KPIs.

  4. 4

    Fix the sources and measure again

    Work on what the answers actually rely on: your own pages, third-party sources, and the domain readiness signals AI crawlers read. Then re-run and compare against the previous run.

Research

From AI visibility data to practical playbooks.

The public site can become the base for methodology notes, benchmark research and product education.

Method noteWhat makes a source visible inside AI answers?Method noteHow the Lighthouse KPI model scores brand presenceMethod noteDomain readiness checks for AI crawlers and citations
FAQ

Questions we get asked about AI visibility.

Short answers to what teams ask before they start measuring how AI engines describe their brand.

  • What is AI visibility?

    AI visibility is how often and how favourably a brand appears inside answers generated by AI engines such as ChatGPT, Gemini, Perplexity and Claude. Unlike a search ranking, there is no public results page to inspect: the answer is composed for each user, so visibility has to be measured by asking the models directly and analysing what they reply.

  • How does DelveDeep measure it?

    DelveDeep runs structured prompt libraries against several AI engines on a repeatable schedule, then analyses each answer for brand mentions, sentiment, position against competitors and the sources cited. Results are scored with Lighthouse-style KPIs so two runs taken weeks apart can be compared directly.

  • Which AI engines does DelveDeep cover?

    The measured panel includes ChatGPT, Gemini, Perplexity and Claude, plus rotating coverage of DeepSeek, Meta AI, Qwen, Copilot and Google AI Overviews. Engine choice matters by market: buyers in China or Japan often use models that are absent from European reporting.

  • Why do AI engines cite some sources and not others?

    Models favour sources that are reachable, well structured and consistent with the rest of the web. DelveDeep audits which pages actually shape the answers about a brand, whether those pages are owned or third-party, and whether the domain is technically readable by AI crawlers.

  • Is AI visibility the same as SEO?

    No. SEO optimises for a ranked list of links, AI visibility optimises for being named and cited inside a generated answer. The technical foundations overlap — crawlability, structured data, clear content — but the measurement and the outcome are different.

  • Who uses DelveDeep?

    Marketing teams, agencies and decision makers who need evidence rather than anecdotes about how their brand, products or locations are represented in AI-mediated discovery.

Company

A product by NextMind.

DelveDeep is built for teams that need a clear view of how brands, places and products are represented in AI-mediated discovery. It is developed by NEXTMIND S.R.L..

Transparent scoring Domain intelligence Actionable reports
P.I. 01654240496Registered office: Via Grande - 57123 Livornoinfo@nextmind.it