AI Software Trial Scorecard
Compare actual tested tasks, accepted results, time including human review and monthly prices (when known). Compare the same task set and acceptance criteria. Keep vendor claims and affiliate promotions separate from your test evidence. No account, API or data upload.
Evidence summary
Before your business buys an AI subscription
- Repeat the same representative tasks and acceptance criteria. Include the time staff spend checking, editing or rejecting outputs.
- Review the vendor's current data processing agreement, retention and deletion rules, use of inputs for model training, subprocessors and any required data-location terms. Do not use sensitive company data without approval.
- Check permission controls, account security, export options and whether the team can stop using the tool without losing essential work.
- Confirm seat minimums, usage limits, overage fees, taxes, trial expiration, renewal and cancellation terms in writing.
- Choose only after comparing the evidence, permitted data use and full contract. Commission payments must not change this assessment.
This is an arithmetic trial worksheet, not an endorsement, academic judgment or money-savings guarantee. Fewer than 20 attempted tasks will trigger a preliminary-evidence warning; 20 is only a practical review prompt, not a statistical guarantee. Actual performance, extra usage limits, data processing, compliance and billing terms require independent verification. Affiliate payment must never determine the ranking.
Worked decision: speed and subscription cost can point in different directions
Imagine two fictional tools tested on the same 20 representative tasks. Tool A has 18 accepted results and averages eight minutes per attempted task, including all review and rework. Its 160 minutes divided by 18 accepted results is about 8.89 minutes per accepted result. Tool B has 16 accepted results at six minutes per attempted task: 120 divided by 16 is 7.5 minutes per accepted result. A shorter generation time alone would not establish either result.
At a scenario of 50 comparable attempts per month, those observed acceptance fractions imply 45 accepted results for A and 40 for B. If their hypothetical monthly subscriptions are $30 and $40, subscription cost per expected accepted result is approximately $0.67 and $1.00. B uses fewer observed minutes per accepted output; A has the lower subscription-only figure. Neither observation establishes better output quality or a universal purchase winner.
Record the conditions of the test
Use the same task difficulty, accepted-output definition and timing method. Time every attempt, including rejected work, rather than timing only the best demonstrations. Keep a note of the product version, trial date, sample selection and reviewer. A small or biased sample cannot establish future performance; the 20-task warning here is only a practical review prompt, not a statistical confidence threshold.
Only a tool with an explicitly approved data-use review and accepted work is included in the time comparison. A blank price remains unknown. The vendor approval guide covers permissions before trials; the Business AI ROI Calculator covers a different question: valuing one ongoing workflow against its manual baseline. This scorecard compares observed trials of two tools and does not connect to either vendor.
Method context: NIST Generative AI Profile provides a voluntary risk-evaluation framework. The arithmetic and fictional examples on this page are Lynara methods, not NIST ratings or a certification.