How to Choose an AI Service Provider
Not every AI provider fits every workflow. Use this guide to evaluate fit, risk, and long-term partnership.
Assess real capabilities
Request proof-of-concept tasks tied to your workflows. Evaluate accuracy, latency, and failure modes rather than marketing claims.
Check integration readiness
Confirm compatibility with your data sources, APIs, identity provider, and security stack. Integration complexity drives hidden costs.
Review data governance
Understand data retention, model training policies, and privacy controls. Verify compliance with your industry requirements.
Evaluate support model
Support should cover deployment, monitoring, and incident response. Ask for escalation paths and response-time commitments.
Compare total cost of ownership
Include implementation, inference, storage, support, and refresh cycles. Lowest price often hides operational debt.