Executive summary AI vendor demos optimize for excitement, not operability. Before procurement, evaluate integration effort, evaluation methodology, data handling, and who owns production support after go-live. Findings 1. Integration scope is routinely underestimated — plan for API limits, auth models, and exception queues. 2. Accuracy metrics in demos rarely match production document variance. 3. Governance requirements in regulated industries need explicit human-in-the-loop design. Recommendations Use a weighted scorecard covering technical fit, operational ownership, and exit strategy. Run a bounded pilot on real documents with agreed success criteria before enterprise licensing.
Knowledge
Research
Evaluating AI Vendors Without Buying the Demo
A due diligence checklist for executives reviewing AI platform proposals — accuracy, integration, and operational fit.
Shabbir Ahmed
Founder & Principal Engineer
Key takeaways
What to remember
- Executive summary
- AI vendor demos optimize for excitement, not operability. Before procurement, evaluate integration effort, evaluation methodology, data handling, and who owns production support after go-live.
- Findings
- Integration scope is routinely underestimated
- Accuracy metrics in demos rarely match production document variance.
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