The biggest question in AI infrastructure right now isn’t what to build — it’s whether to build at all. We run our entire operation on a single GCP instance with MCP servers and custom pipelines at near-zero marginal cost. But that approach isn’t right for everyone.
This simulator models three scenarios — 100% SaaS/API, Hybrid with MCP servers, and Full Build — and calculates monthly costs, 3-year total cost of ownership, and break-even timelines based on your actual numbers.
Input your current marketing spend, team size, and content volume to see which infrastructure approach delivers the best ROI for your situation.
AI Infrastructure ROI Simulator
Build vs Buy vs API: What’s Right for Your Team?
Your ROI Comparison
3-Year Total Cost of Ownership
Break-Even Timeline
When Full Build investment is recovered through API cost savings
Now
Month 18
36 months
Hidden Costs to Consider
Vendor Lock-in: SaaS/API providers can increase pricing or shut down services. Full Build gives you control.
Scaling Limitations: API rate limits and costs scale directly with volume. Full Build scales incrementally.
Maintenance Burden: Full Build requires ongoing updates, security patches, and infrastructure management.
Knowledge Silos: Custom systems create dependency on specific developers. SaaS is more portable.
Integration Costs: All scenarios require integration time. Full Build often requires more custom work.
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