5 October 2026
AI discoverability tool
An AI discoverability tool finds where your website appears inside Artificial Intelligence outputs and produces visibility reports showing what AI says…
AI discoverability tool
How to choose and use an AI discoverability tool for your website
An AI discoverability tool finds where your website appears inside Artificial Intelligence outputs and produces visibility reports showing what AI says, which sources it cites, and where those answers diverge from your facts. SaidTrue provides those visibility reports and public scorecards by scanning major AI engines so you can prioritise corrections and authoritative citations.
What an AI discoverability tool does
An AI discoverability tool maps how your website and business appear inside outputs produced by Artificial Intelligence, capturing the text of answers, any sources cited, and differences from your verified information. SaidTrue gives visibility reports for a website's presence in AI search and publishes scan results such as public scorecards for reviewed businesses.
Why SaidTrue's AI discoverability tool matters for your business
Why SaidTrue's AI discoverability tool matters is that customers increasingly ask AI systems who to use and what a business is like, so what AI says can influence reputation and demand. SaidTrue helps you see those AI descriptions, the evidence AI cites, and where AI statements diverge from the truth so you can prioritise fixes.
How SaidTrue scans and reports AI outputs
How SaidTrue scans and reports AI outputs is by asking ChatGPT, Gemini, Perplexity and Claude the customer-style questions your audience would ask, then showing what was said, what was sourced, and where the truth diverges. SaidTrue offers free scans and public scorecards and can support ongoing monitoring and a verified AI profile.
How to evaluate an AI discoverability tool before you buy
How to evaluate an AI discoverability tool includes checking whether the tool runs representative buyer-intent prompts across multiple AI platforms on a regular cadence and whether it tests multiple prompt variations to reduce noise, as explained by Discovered Labs. How to evaluate an AI discoverability tool also requires verifying that the tool identifies the URLs that AI models cite so you can understand and protect your source of AI visibility, as noted by Sedestral.
How to act on a SaidTrue visibility report
How to act on a SaidTrue visibility report is to review each AI-cited source, correct or clarify the cited pages on your site, and add authoritative content or structured data so future AI answers can cite accurate sources. How to act on a SaidTrue visibility report also includes publishing or maintaining a verified AI profile and scheduling follow-up scans to confirm that corrections appear in subsequent AI outputs.
Limitations of an AI discoverability tool
Limitations of an AI discoverability tool include the fact that large language models are non-deterministic and sensitive to prompt wording, so no tool can promise simple, deterministic tracking or guaranteed placement in AI answers; Discovered Labs warns that such promises indicate a misunderstanding of how LLMs work. Limitations of an AI discoverability tool also mean reports are diagnostic: they show where AI currently cites you or errs, but they do not directly change the behaviour of third-party AI systems.
Getting started with SaidTrue
Getting started with SaidTrue is to run a free scan to generate a public scorecard, inspect the report for cited sources and factual divergences, and opt into ongoing monitoring or a verified AI profile if you want continuous coverage. Getting started with SaidTrue gives you a baseline that you can use to prioritise content fixes, citation controls, and monitoring cadence.
Common questions
Which AI engines does SaidTrue scan?
SaidTrue scans ChatGPT, Gemini, Perplexity and Claude and reports what each engine says about your business, the sources cited, and any factual divergences found in the answers.
Can SaidTrue fix incorrect information that AI shows about my business?
SaidTrue does not directly change how third-party AI systems answer, but SaidTrue's reports show the incorrect statements and the sources AI used so you can correct your website content, add authoritative citations, or publish a verified AI profile to influence future answers.
How often should I run an AI discoverability scan?
You should run AI discoverability scans on a regular cadence and after major website or business-data changes so you detect new citations or fresh errors; Discovered Labs describes regular cadence and repeated prompt testing as the core job of visibility tools. Repeat scans let you measure whether your corrections change AI behaviour over time.
Will using an AI discoverability tool guarantee my site appears in AI answers?
No; because large language models vary with prompt wording and context, no tool can guarantee inclusion in AI answers, and any promise of deterministic placement is misleading, as explained by Discovered Labs. An AI discoverability tool can, however, show where you currently appear and help you improve the signals that increase the chances of being cited.
How SaidTrue approaches AI discoverability tool
For SaidTrue, "AI discoverability tool" means "Artificial Intelligence". We take that definition literally and build our process around what AI systems actually say about a business online. Our work is first-hand: we run the same inquiries a prospective customer would, gather the AI responses, and show where those responses line up with verifiable facts.
Common problems customers face
Customers commonly find three recurring issues: AI outputs that omit or misidentify their business, answers that cite third‑party sources without clear attribution, and high sensitivity to prompt phrasing that produces inconsistent representations. We regularly see engines that cannot confidently identify a business, and we surface those gaps so they can be addressed in content and profiles.
Method and steps we take
Our workflow reflects practical, repeatable steps. First, we simulate buyer-intent queries across multiple AI engines—asking the same questions users would ask—then capture the full responses and the sources those engines reference. This approach follows the core pattern described by Discovered Labs: "running a representative set of buyer-intent prompts across multiple AI platforms on a regular cadence, then capturing which brands appear and in what context" (AI Visibility Tools: Maximize Search Presence With Discovered Labs, Discovered Labs, https://discoveredlabs.com/blog/ai-visibility-tools-maximize-search-presence-with-discovered-labs). Next, we map which URLs and pages the AIs cite, because tracking citation sources is essential to understanding where AI‑derived visibility comes from. As Sedestral notes, reliable tools identify which URLs models reference and flag when models generate incorrect information (Best ai search visibility tools: features, pricing, use cases, Sedestral, https://sedestral.com/en/blog/ai-search-visibility-tools). Finally, we compare statements to verified facts about the business and annotate divergences—the where, what, and why of incorrect or absent information.
Outcomes customers can typically expect
Customers receive a visibility report that explains which AI engines mention them, which sources those engines rely on, and where discrepancies with the truth occur. Typical outcomes are clearer prioritization for content fixes, identification of high‑impact source pages to improve, and an objective scorecard that shows where AIs fail to identify or misdescribe the business. Because our scans use the same prompts customers use, the reports make the downstream remediation work—content updates, structured data, and source improvements—directly actionable.
References
- AI Visibility Tools: Maximize Search Presence With Discovered Labs — Discovered Labs
- Best ai search visibility tools: features, pricing, use cases — Sedestral
Sources and supporting material
Further reading: