Choose with evidence
AI automation decisions, explained.
Compare billing models, diagnose knowledge problems, and define what success looks like before choosing a tool. Every guide includes source links and a reproducible pilot plan.
n8n vs Make vs Zapier: choose by workflow, billing unit, and ownership
Compare execution, credit, and task billing with a worked workload example and a practical evaluation plan. No universal cheapest-tool claim.
Read the decision guide →RAG vs fine-tuning: a decision guide for business knowledge
Separate missing knowledge from inconsistent behavior, then test retrieval, permissions, citations, and abstention before training a model.
Read the decision guide →AI agent vs workflow automation: how much autonomy does your task need?
Choose between fixed rules, an AI step, and an agent using uncertainty, reversibility, and measurable task success.
Read the decision guide →How to evaluate an AI customer support bot before launch
A reproducible support-bot pilot: test answerable questions, outdated policies, missing evidence, access boundaries, and safe handoff.
Read the decision guide →How to get cited in AI search: a measurable publishing checklist
A practical checklist for Google AI features, Bing, and Copilot: crawl access, source evidence, canonical URLs, clear answers, and citation measurement.
Read the decision guide →Put the decision into numbers.
Calculate capacity value or export an agent evaluation scorecard. Free, no account required.
Open the free tools →