AI Vendor Comparison Scorecard

Score AI vendors against your enterprise requirements

Ad placeholder (leaderboard)

AI vendor comparison scorecard

Choosing an AI vendor on vibes is how organisations end up locked into a contract that fails the security review six months later. This scorecard makes the choice explicit: you declare what matters and how much, score each vendor on those criteria, and the tool ranks them by a weighted total. The output is a defensible artifact you can drop straight into a procurement deck.

How it works

You start with common enterprise criteria — security & compliance (SOC 2 / ISO 27001), data residency, uptime SLA, context window, price, support, and ecosystem maturity — each with an importance weight from 1 to 5. Then you score each vendor 1–5 on every criterion. For each vendor the tool computes a weighted sum (score × weight, summed across criteria) and normalises it to a percentage of the maximum achievable, then ranks vendors highest-first. Add or remove rows to match your real shortlist and RFP.

Tips and notes

Set the weights before you score the vendors — deciding priorities while staring at the scores invites bias toward a favourite. Reserve a weight of 5 for true dealbreakers (a missing SOC 2 report should sink a vendor regardless of how good the demo was). Score from evidence, not marketing: trial the models, read the DPA, and ask for the actual SLA credit terms. When two vendors finish within a few points, the ranking is a tie — break it on a hands-on pilot or contract flexibility, not by nudging a score. Everything stays in your browser, so you can iterate freely.

Ad placeholder (rectangle)