Questions to ask, red flags to watch for, and a structured way to compare AI vendors. Because the slickest demo doesn't always mean the best solution.
Does this vendor actually solve the problem you defined?
Can the vendor demonstrate their solution working on a problem similar to yours (not just a generic demo)?High Weight
Does the vendor understand your industry and its specific requirements?
Is the solution appropriately scoped, or is it trying to do everything?
Can the vendor clearly explain what the solution will NOT do?High Weight
Where does your data go and how is it protected?
Does the vendor clearly document where your data is processed and stored?High Weight
Is your data used to train the vendor's models?High Weight
Does the vendor meet your compliance requirements (SOC 2, HIPAA, GDPR, etc.)?High Weight
What happens to your data if you leave the vendor?
Does the vendor have a documented incident response plan?
What will this actually cost, including what they don't mention?
Is the pricing model clear and predictable?
Does the vendor account for data preparation, integration, and training costs?High Weight
What are the contract terms and exit costs?
Can the vendor connect you with customers who have been using the product for 12+ months?High Weight
What does deployment look like, and what happens after?
Does the vendor provide a realistic implementation timeline?
What ongoing support is included vs. extra cost?
Who handles maintenance, updates, and model retraining?
Does the solution integrate with your existing systems?High Weight
Will this vendor be around in 3 years?
How long has the vendor been operating, and what is their funding/revenue situation?
Does the vendor have a public product roadmap?
What is the vendor's customer retention rate?
Too many unknowns or weak areas. Go back to the vendor with specific questions, or evaluate alternatives.
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AI Vendor Evaluation Framework by MindXpansion | mindxpansion.ai
Engineering Discipline. Business Intelligence.