Methodology & data sources

Jobscanner focuses on employment-risk around recruiter and employer phone numbers — not generic caller-ID lookup.

• In-app reviews from registered and anonymous users on JOB SCANNER, including structured trust marks and experience details.
• User scans when someone checks a number on the site; scan history helps prioritize enrichment but does not alone publish a public dossier.
• External review aggregators (see Sources below): we cache publicly available UGC from selected sites into our pipeline with a TTL; raw payloads are stored for aggregation, not copied as endorsements.
• VirtualScan pipeline may publish a curated in-app review when donor thresholds are met — still subject to the index gate below.

We combine these layers into one phone dossier. Missing data on one layer does not erase signals from another.

A phone page is eligible for the public catalog, sitemap, and search indexing only when at least one of these is true:

• A — a real user (registered or anonymous) scanned the number on Jobscanner.
• B — an in-app review from a real user exists for that number.
• C — a published virtual in-app review (Avatar Factory) exists for that number.

Not indexed: a number that appears only in donor cache (phone_reports) or parser-sync queue without B or C remains available at a direct URL but carries noindex — we do not treat thin single-source cards as the product.

This gate applies consistently to feeds, sitemaps, and SEO APIs.

AI Recruiter is a post-scan dialogue: after you check a recruiter or employer number, the chat helps interpret the multi-source dossier in a job-search context and suggest next steps — including CV drafting in conversation.

• Answers draw on phone intelligence (reviews, summaries, risk patterns) plus curated platform knowledge retrieved into the prompt.
• The chat does not browse arbitrary websites live during a reply.
• Output is decision support, not legal advice and not a safety warranty. The model can still err; you remain responsible for decisions about pay, travel, and documents.

Learn more about the product on About; this page explains the data layer behind it.

Jobscanner does not fine-tune or train its own large language model on your chats or on scraped reviews. We use a foundation model (for example Gemini or a key you provide) with retrieval and grounding: relevant dossier fields and approved knowledge snippets are inserted into the prompt at answer time.

Updating corpora, summaries, and dossiers improves answers without retraining model weights. Consumer-facing copy describes this as platform data + language model — not as a proprietary trained brain.

• No reviews yet on Jobscanner does not mean a recruiter is safe — it may mean the number was not checked or no one shared an experience.
• Negative community marks are reports, not court verdicts or government findings.
• AI summaries and chat replies synthesize available signals; they are not legal certification of an employer.
• Donor-site comments are third-party UGC; we aggregate them but do not verify each claim individually.
• Pattern alerts (prepaid fees, document requests, etc.) are heuristics aligned with fair-recruitment guidance — not automatic fraud convictions.

Use Jobscanner as one input before you pay fees, share documents, or travel for work:

• Cross-check the recruiter, company name, and payment details through independent channels.
• Guest viewers may see masked review details; sign in for fuller context where policy allows.
• Phone checks for non-Premium users consume trust points; guest scans are limited by bot protection and rate caps — not unlimited free lookups.
• Trust percentages reflect in-app trust marks among reviews that include them — not a guarantee of future behavior.

When in doubt, pause the transaction and use official labour or consumer-protection resources in your country.

We treat the sites below as external data sources for employment-related phone UGC. Listing them explains provenance; it is not an endorsement of their moderation, accuracy, or legal status.

• moshennik.eu — labour and scam-related phone/company comments (RU-focused UGC).
• vashe-mnenie.com — company and phone review aggregation.
• telefonnyjdovidnyk.com.ua — Ukrainian phone directory with danger/community signals.
• Facebook group signal — selected blacklist threads inform internal risk signals; we do not mirror or index Facebook content as Jobscanner pages.
• otzyv.eu — deprioritized donor; may appear in legacy cache only.

Donor availability varies by number and region. A missing donor row does not imply the number is trustworthy.

If information about you or a number is wrong, outdated, or mislinked:

• Submit a correction via Report a scam / dispute.
• Contact support through Contacts.
• Read how we handle personal data in our Privacy Policy.

We review good-faith requests but cannot remove factual user experiences solely because a party disagrees with them.