Evidence before output
Our process is designed around current service documentation, observable signup and product flows, published pricing, privacy and safety policies, and hands-on observations only when explicitly identified. We do not present a copied archive page, a merchant description, or an AI-generated draft as completed research.
- Confirm the service is active. We verify the official product, supported markets, access method, and operator before reviewing it.
- Map the intended audience. Relationship intent, location, age requirements, identity, and community focus shape whether a service is relevant.
- Check real access and cost. We distinguish free registration from usable communication and record subscription or credit limitations.
- Inspect safety and privacy. Blocking, reporting, verification, data handling, moderation claims, and account deletion are reviewed separately from marketing language.
- State the evidence level. Desk research, observable product checks, and hands-on use are not presented as if they were the same thing.
Research, experience, and opinion
We distinguish direct observation from second-hand information. When we have not personally used or tested something, we say so through the wording and production notes. Editorial judgment is explained with criteria instead of being disguised as an objective fact.
Use of AI and automation
Automation may assist with source organization, transcription, structured comparisons, grammar, or an initial draft. It may not publish autonomously. A human editor is responsible for checking claims, links, dates, relevance, originality, and whether the page adds value beyond its sources. Materially AI-assisted pages are marked in their production notes.
Updates
Pages are reviewed when source facts change, a reader reports a material issue, or the topic becomes stale. The visible updated date must reflect a meaningful change to the main content, evidence, structured data, or useful links rather than an automatic date refresh.