For brand managers Hear how AI describes your brand. Then shape it.

Seerly scores how AI assistants describe your brand on a fixed prompt set, splitting every tracked answer into positive, neutral, negative, and mixed, and keeping the response text behind each score.

The point of difference from visibility tracking is tone. A brand can be mentioned constantly and still be framed in terms you would never choose.

• Sentiment split per prompt, per engine, per run
• Aspects pulled from the answers themselves, such as quality, service, or pricing
• Mention volume per aspect, so one complaint is not read as a trend
• Scheduled runs every 4 days on Basic, and more frequently on Pro

Aspect-level detail is usually where an overall score becomes something a brand team can act on.

Seerly shows the exact sources an engine cited when it produced the inaccurate answer, which turns a vague reputation problem into a specific list of pages carrying the wrong claim.

AI assistants do not invent a brand description from nothing. They summarize what they can find, so a wrong answer usually points at a stale or misleading source.

• The verbatim response, the engine that returned it, and the run date
• Every URL cited alongside that answer
• Whether the source is a page you own, a marketplace, a review site, or a reference site
• The same prompt on earlier runs, to see when the framing changed

Owned sources can be corrected directly. For third-party sources the practical route is publishing a clearer, better-cited alternative.

AI engines assemble a brand description from public sources they can reach and parse, then write a summary. The sources they lean on decide the framing far more than any single page you control.

This is why two engines can describe the same brand differently. They are not reading the same set of pages.

• Seerly records the cited URLs behind every tracked answer
• Sources are grouped by type: owned pages, marketplaces, reviews, references
• Each engine is reported separately, never blended into one narrative
• Changes between runs show when a new source starts influencing the answer

Reading the source mix first tends to be more useful than reacting to the wording of any one response.

Yes. Seerly scores sentiment independently on ChatGPT, Perplexity, and Google AI Overview, and never averages them together, so a weak result in one engine stays visible.

Separate scoring matters because engines draw on different sources, and a souring narrative often appears in one place well before the others.

• Basic: one engine of your choice, either Google AI Overview or ChatGPT
• Pro: all three, ChatGPT, Perplexity, and Google AI Overview
• Enterprise: additional engines on request, under a custom scope
• Per-engine sentiment movement across 7 day, 30 day, and 3 month windows

Brand teams generally prioritize the engine where the framing is weakest rather than working on an average that flatters the problem, since that is where the correction has the most room to matter.

Social listening reports what people said about your brand. AI brand monitoring reports what an AI assistant tells a prospective buyer when they ask about your category, which is a synthesized answer rather than a mention.

The difference is reach per source. A single outdated page can shape the description an assistant repeats to everyone who asks.

• Measured on tracked buyer questions, not on a stream of public posts
• Every score opens into the full response the engine returned
• Cited sources are recorded, so the cause of a shift is traceable
• Runs are scheduled, so history is comparable rather than sampled

Most brand teams run both. They answer different questions about the same reputation.

Yes. Seerly records the competitor brands that appear in the same AI answers as yours, along with how each is framed, so the comparison is drawn from identical prompts and runs.

That matters for positioning work, because the interesting finding is rarely a score. It is the attribute an assistant attaches to a competitor and not to you.

• Share of voice across your tracked prompt set, per engine
• Aspect-level framing for each brand in the comparison
• Prompts where a competitor is recommended and you are absent
• The citation sources behind each competitor mention

The competitor set is yours to define, so benchmarking stays against the brands you actually lose deals to.

Yes. Every sentiment score in Seerly opens into the full response that produced it, with the engine, the run date, the aspect it was counted under, and the URLs cited alongside it.

For negative results the label is rarely the useful part. The sentence is, because that is what a buyer would have read.

• Full response text per run, attributed to the engine that returned it
• The aspect the score was attached to, such as pricing or service
• Every cited URL from that answer
• The same prompt on earlier runs, for direct comparison

Only publicly available AI responses and public web pages are analyzed to build this view, and the stored results stay private to your account.

None. Seerly analyzes your public website pages and public AI engine responses, so there is no code to install, no pixel, no DNS change, and no SDK.

For a brand team this usually removes the longest step in adoption, because there is no integration review to schedule before the first run.

• No access to analytics, CMS, ad accounts, or customer data
• No customer records or logged-in data is collected
• Analysis results are private to your account
• An optional WordPress connection on Pro, only if you choose to publish drafts

Seerly is operated by K4 Minds Technologies LLP, and the details of what is stored and for how long are set out in the privacy policy rather than summarized here.