An enterprise AI procurement evaluation framework
Test data handling, identity, model access, integration, observability, portability, support, and exit obligations before scoring vendor promises.
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Guidance library
AI procurement
Evaluate provider, data, integration, security, and exit requirements before purchase.
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Reviewed enterprise architecture guidance
Narrow the library by controlled topic, audience, pillar, or API product.
Build versus buy for enterprise AI infrastructure
Compare control, differentiation, integration depth, security, time, maintenance, switching cost, and the team's ability to operate what it owns.
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