AI Tool Profile

Bluerails Discovery: Methodology, Pricing, and Evaluation

Bluerails Discovery measures how four AI assistants mention, cite and shortlist a business using repeated queries, confidence intervals and industry-specific visibility weights.

Analyst comparing repeated AI discovery observations around a boutique hotel model
Company
Bluerails
Primary category
AI Ecommerce Tools, AI Research Tools
Best for
Marketing, hospitality, publishing, SaaS and ecommerce teams that want a repeatable AI-discovery baseline before investing in content or agent-readiness work.
Pricing
One free report per domain. Paid Discovery is €119 monthly or €99 per month billed annually; Discovery+ is €299 or €249 annually; Action is €1,999 or €1,799 annually. Settlement is coming soon.
Free plan
yes
API
Unknown
Open source/open weight
Unknown
Linked launches
1
Latest launch date
June 23, 2026
Last verified
2026-07-27

Verification & Sources

Status
Verified
Source links
4
Freshness
Verified July 27, 2026
Last verified
July 27, 2026
Last updated
July 28, 2026
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What It Does

Bluerails Discovery measures how four AI assistants mention, cite and shortlist a business using repeated queries, confidence intervals and industry-specific visibility weights.

Full Guide

Kingy verdict: Bluerails Discovery is more credible than a one-shot “AI visibility score” because its published method repeats prompts and exposes uncertainty. It is still a vendor-designed measurement product, not proof that higher visibility will produce bookings or revenue.

What the product measures

The free report queries ChatGPT, Perplexity, Gemini and Claude. Bluerails says each prompt is run five times per engine, producing hundreds of observations for a company rather than treating one stochastic response as stable. The methodology defines selection rate, share of voice, citation rate and discovery gap, then combines eight KPIs using weights that vary by industry. A hotel, publisher, SaaS vendor and ecommerce store therefore do not receive an identical weighting model.

The site also checks five public machine-readability signals: llms.txt, named AI-crawler directives, Schema.org JSON-LD, a well-known MCP manifest and a sitemap. Each signal contributes equally to the readiness component. A failed fetch or non-200 response counts as absent. That is easy to understand, but it also means availability, timeouts and implementation conventions can affect a score independently of whether an assistant actually uses the signal.

Method strengths and limits

Repeated sampling and bootstrap 95% confidence intervals are a meaningful improvement over a single snapshot. The method also keeps earlier score-model versions visible rather than silently recalculating old reports. The harder questions concern prompt selection, competitor sets, geographic and language coverage, model-version drift and the mapping from mentions to attributable commercial outcomes. Bluerails cites research for its methodology, but Kingy did not rerun the queries or verify its aggregate comparisons with competing products.

Use the free report as a diagnostic baseline. Review the actual prompts, rerun a small sample manually, inspect citations and separate branded recognition from open-category discovery. If a score changes, ask whether the movement exceeds the confidence interval and whether the cited pages or conversion path changed. A site can become more machine-readable without becoming more persuasive or bookable.

Pricing and buying decision

One free report is available per domain without a card. The current company page lists Discovery at €119 monthly or €99 per month billed annually, Discovery+ at €299 or €249 annually, and Action at €1,999 or €1,799 annually. Settlement is marked coming soon. The free report, paid visibility tracking, site-readiness work, booking execution and stablecoin settlement are different product stages; buyers should not infer maturity in one layer from evidence about another.

How Kingy would evaluate it

Choose ten commercially important prompts across branded, comparison and open-discovery intent. Record the exact engine, date, locale and candidate set. Compare Bluerails’ repeated results with an independent rerun, then inspect whether recommended changes alter citations and qualified referral or booking behavior over several weeks. Stop if the workflow optimizes the composite while real discovery paths remain unchanged.

Kingy reviewed the live report flow, methodology, pricing and separate payments documentation. We did not submit a customer domain, reproduce a confidence interval or validate a booking outcome.

Preserve the raw observations alongside each score so later audits can separate source changes, model drift and scoring-model revisions.

Primary sources

Launch History

AI Ecommerce Tools

Bluerails Discovery

Bluerails launched Discovery, a free per-domain report that repeats prompts across ChatGPT, Perplexity, Gemini and Claude and presents AI-visibility metrics with uncertainty ranges.

Verified Free: Yes API: No Open: No
Product Hunt tractionClear use caseBeginner-friendlyCreator-friendly
Kingy
7.3 / 10
Demo
Not scored yet
YouTube
Not scored yet

Repeated sampling and published confidence intervals make Discovery more useful than a one-answer snapshot. The remaining risk is outcome validity: Kingy did not reproduce…