Lantad versus Otterly.AI
Otterly.AI tracks what AI engines already say about your brand; Lantad measures and fixes whether AI crawlers can read your site in the first place.
Lantad and Otterly.AI answer different questions about AI search. Otterly.AI tracks what AI engines already say about your brand; Lantad measures and fixes whether AI crawlers can read your site in the first place. The table below sets the two side by side, dimension by dimension, and the section after it names the cases where Otterly.AI is the better tool.
Competitor claims on this page come from Otterly.AI's own published material, last checked on 24 July 2026. Lantad's own figures are read from the configuration the product enforces.
Choose Otterly.AI when your main question is what AI is saying about you. If you need continuous monitoring of brand mentions and citations across many consumer assistants, compare share of voice against a competitor roster you define, watch sentiment over time, run prompt research, or roll all of that into client-facing reports across countries and languages, Otterly.AI is built for that job and Lantad is not.
Choose Lantad when you need to know whether AI can read your pages at all, and fix it. If a monitoring tool shows you are absent from AI answers and you want to find out why, Lantad diagnoses the cause at the source: content that only renders in JavaScript, robots.txt blocking a specific crawler, thin or missing structure and schema, poor retrievability.
Otterly.AI and Lantad both sit in the AI-visibility space, but they work on different layers. Otterly.AI is an AI search monitoring platform: it watches how your brand shows up inside AI answers across engines its site lists as ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, Microsoft Copilot, and Claude, tracking mentions, citations, share of voice, and sentiment over time.
Lantad works one layer upstream. It measures whether AI crawlers can reach and parse your pages at all, then fixes what it finds. The two are complementary. If you want to know what AI is saying about you, Otterly.AI is built for that. If you want to know whether AI can read your pages well enough to cite them accurately, that is Lantad's job.
What Otterly.AI does
Otterly.AI is an AI search monitoring tool. Its core job is tracking brand visibility inside AI-generated answers: how often a brand is mentioned, which domains and pages get cited as sources, how it compares to competitors (share of voice), and the sentiment of those mentions. Its site lists engine coverage of ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, Microsoft Copilot, and Claude (some third-party reviews describe Claude, Gemini, or AI Mode as add-ons, so tier packaging may vary and can change). It supports many countries and languages, and adds prompt research, reporting, CSV export, a Looker Studio connector, an API, and an MCP server. It also ships supporting technical features including a crawlability checker, a content audit, and agent analytics (described on its site as a closed beta) that report which AI crawlers visit a site.
What Lantad does
Lantad is an AI-visibility scanner focused on machine readability. It fetches a page the way an AI crawler does (raw HTML, no JavaScript) and again in a real browser, diffs the two, and scores whether crawlers can actually reach and read the content: Prose Parity (how much text survives without JavaScript), Access (robots.txt rules per named crawler), Retrievability, Structure, and Schema, rolled into a 0 to 100 score. It then fixes the problems it finds through a Deep Audit, a Fix Sprint, and ongoing monitoring. Lantad also runs a narrower answer-side surface called prompt tracking: questions derived from your own page go to up to 8 answer engines (official APIs, an open-weight chain, and Google AI Overviews captured from the public SERP through a vendor), and it reports naming, the other brand names those answers produced, a share of the names produced, cited source hosts, and a sentiment signal that is model-graded on paid plans with a labelled word-list fallback. It does not monitor consumer assistants across countries and languages. Rival names are extracted from the answers, and since August 2026 paying accounts can also pin a small competitor roster that keeps chosen rivals listed even at zero mentions: persistence and labelling on Lantad's own runs, not consumer-app monitoring. Its main lane is the readability layer underneath, which is what any downstream citation depends on.
Side by side
Rows are the dimensions the two tools actually differ on. A cell that states Yes, No or Partly carries that word as a chip with the vendor's own qualifier beside it; every other cell is quoted as prose, because a chip that decides a capability the vendor never claimed would be a claim we cannot defend.
| Dimension | Otterly.AI | Lantad |
|---|---|---|
| Primary job | Monitor what AI engines say about a brand: mentions, citations, share of voice, sentiment | Measure and fix whether AI crawlers can reach and read a page |
| Layer | Output layer: the answers AI already generates | Machine-readability layer: raw HTML vs rendered diff, upstream of citation |
| Core method | Runs prompts across AI engines and records how the brand appears over time | Fetches page as a crawler and as a browser, diffs them, scores parity, access, retrievability, structure, schema |
| Engine coverage | Broad: site lists ChatGPT, Google AI Overviews, AI Mode, Gemini, Perplexity, Copilot, Claude | Evaluates crawler access per named bot via robots.txt; prompt tracking asks up to 8 engines (official APIs, an open-weight chain, and Google AI Overviews via public-SERP capture), in one language and one location |
| Fixing | Includes crawlability check and content audit with recommendations | Full remediation workflow: Deep Audit, Fix Sprint, ongoing monitoring |
| Reporting extras | Multi-country and language, CSV export, Looker Studio, API, MCP server, agency workspaces | 0 to 100 readability score with per-check breakdown |
Where Otterly.AI is better
Choose Otterly.AI when your main question is what AI is saying about you. If you need continuous monitoring of brand mentions and citations across many consumer assistants, compare share of voice against a competitor roster you define, watch sentiment over time, run prompt research, or roll all of that into client-facing reports across countries and languages, Otterly.AI is built for that job and Lantad is not. Agencies managing multiple brands and marketing teams reporting on AI-answer presence are its natural fit.
Where Lantad is better
Choose Lantad when you need to know whether AI can read your pages at all, and fix it. If a monitoring tool shows you are absent from AI answers and you want to find out why, Lantad diagnoses the cause at the source: content that only renders in JavaScript, robots.txt blocking a specific crawler, thin or missing structure and schema, poor retrievability. It measures those precisely and remediates them. Many teams use both: Lantad to make pages readable, a monitor like Otterly.AI to watch what happens in the answers afterward.
How Lantad works
Four steps, run on every scan, free or paid.
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Fetch as a crawler
One request for the raw HTML, no JavaScript, the way an AI crawler takes the page.
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Render in a browser
The same URL again in a real browser, so the rendered page can be compared with what was delivered.
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Compare the two
Diff the two documents and count the words, headings, links and structured data that only exist after JavaScript.
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Grade and rank
Score access, Prose Parity, structure and schema, then rank the fixes by what moves the score most.
Common questions
Is Lantad an alternative to Otterly.AI?
Not exactly. Otterly.AI monitors what AI engines say about your brand. Lantad measures and fixes whether AI crawlers can read your pages. They address different layers and are often used together rather than as substitutes.
Does Lantad track brand mentions or share of voice across AI answers?
Narrowly, yes. Lantad's prompt tracking reports whether each answer named you, the other brand names those answers produced, a share of the names produced, cited source hosts, and sentiment that is model-graded on paid plans with a labelled word-list fallback, across up to 8 API and open-weight engines in one language and one location. What it does not do is monitor consumer assistants across many countries and languages against a competitor roster you configure, which is what a monitoring tool like Otterly.AI does. Lantad's main focus stays on the machine-readability layer underneath: whether crawlers can reach and parse your content.
Doesn't Otterly.AI also check crawlability?
Yes. Otterly.AI's site lists a crawlability checker and a content audit as supporting features alongside its monitoring. Lantad's whole product is that readability layer, going deeper with a raw-versus-rendered diff, per-crawler robots.txt analysis, parity and structure scoring, and a fix workflow.
How current are the claims about Otterly.AI on this page?
They were last checked against Otterly.AI's own published material on 24 July 2026. Features and pricing change, so confirm anything decision-critical with Otterly.AI directly.