Build costs often underestimate MLOps, connector maintenance, governance, and audit features. Mid-sized teams frequently buy a platform for workflow and governance and keep build for custom integrations only.

Connector upkeep, vector database operations, access control on retrieval, approval UX, audit export, on-call for production failures, and security review for each new tool integration. These often exceed initial model API spend for mid-market timelines.

When you need governed workflows in production within a few quarters, lack a large ML platform team, and must satisfy finance or BFSI audit expectations. Buying prioritizes time-to-evidence over maximum customization.

Yes. Use a platform for governance, connectors, and workflow audit trails; keep custom code for niche calculators, legacy APIs, or industry-specific rules. Define which layer owns logging and approvals so hybrid stacks do not create audit gaps.

Build paths delay audit-ready features; buy paths amortize governance across workflows. ROI comparisons should include months to pass internal audit on the first production process—not only development hours saved on a demo.