You're mid-process on an AI tool decision and the research is sprawling – browser tabs, vendor decks, half-finished spreadsheets, and no clean way to justify the call you're about to make. This scorecard and decision matrix gives you the structured artifact you need to cut through the noise, compare options consistently, and walk away with a defensible recommendation. Built for individual contributors and technical evaluators who need to move fast without looking sloppy. What's included: a single comprehensive document with four fully built-out sections – a Use-Case Fit Classifier, a five-dimension weighted Evaluation Criteria Scorecard, a Side-by-Side Vendor Comparison Matrix supporting up to 10 candidates, and a Decision Recommendation Framework with a fillable written recommendation template. Every section includes worked examples, scoring rubrics, reference tables, and a common-mistakes guide so you know exactly how to use it.
What's included
- A Use-Case Fit Classifier that helps you determine whether a given AI tool or local model actually maps to your specific workflow before you waste time evaluating the wrong candidates
- A weighted Evaluation Criteria Scorecard covering five dimensions – capability, cost, integration, security, and vendor support – so every tool gets assessed against the same standard instead of whatever the vendor chose to highlight
- A Side-by-Side Vendor Comparison Matrix you can populate and present, giving you a shareable artifact that makes your reasoning visible to stakeholders or your future self
- A Decision Recommendation Framework that translates your scorecard results into a structured rationale – not just a ranking, but a justifiable written recommendation you can stand behind in any review meeting
- An Evaluation Reference Guide covering the terminology, tradeoffs, scoring interpretation keys, and common evaluation mistakes you need to avoid the most frequent errors in AI tool selection
