Most enterprise AI systems combine purchased platforms, models, infrastructure, integrations, controls, and custom workflow logic. The useful question is which layers should remain under your control.
Buy standardized capability
Buying fits common requirements where speed, mature operations, support, and predictable functionality matter more than differentiation. Assess data terms, portability, integration, roadmap, security, and exit options.
Build differentiated workflow logic
Custom development makes sense where proprietary context, unusual constraints, deep integration, or strategic process advantage matters. Include ongoing evaluation, monitoring, maintenance, and specialist skills in the cost.
Use a deliberate hybrid
Many strong architectures buy commodity layers while owning prompts, knowledge, workflow, policy, evaluation, and integration. This preserves speed without surrendering the operating logic that differentiates the business.
Make the architecture decision explicit.
Align technology ownership with business value and control.