Our method

How evidence becomes a useful recommendation

A transparent workflow for selecting topics, verifying claims, documenting limits and correcting material errors.

Evidence moves from source documents through verification to a published decision framework.

From question to maintained article

Each stage leaves a visible distinction between sourced facts, evaluation criteria and editorial judgment.

  1. Select
  2. Verify
  3. Test where documented
  4. Publish
  5. Update

Topic matrix

We prioritize questions readers face when comparing AI software and automation: capability, intended use, constraints, ongoing cost and workflow fit. Commercial relationships do not guarantee coverage or a positive conclusion.

Evidence scale and criteria

Claims are weighted by what can support them. Descriptive sources are linked where they materially support a decision.

Vendor documentation — features and current termsIndependent sources — context and limitationsDocumented direct testing — only when explicitly performed

We compare capability, constraints, total cost and intended workflow using the same criteria across options.

Testing and limits

Unless an article explicitly documents a hands-on test, it is research-based. We do not turn vendor claims into first-person experience. Availability, pricing and software features can change, so readers should verify current terms with the provider.

Corrections timeline

Material claims are reviewed when an article is updated. A substantiated error is corrected, and time-sensitive information is refreshed when practical. Readers can report an issue through the contact page.

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