How do you evaluate the total cost of ownership for custom-built AI solutions versus purchased platforms over time?

Every model and solution has a different pricing structure, which makes it difficult to keep up. The future may involve orchestration layers that allow selection of the most cost-effective model per use case. There needs to be an upfront understanding of total cost of ownership to avoid unexpected expenses.

Understanding licensing models is difficult, especially with innovative startups. We attempt to model costs, but the real challenge is building a solid business case before investing time and resources. Proof of concepts help determine if long-term ownership is worthwhile.

Evaluating total cost of ownership is challenging due to varying pricing models, some based on usage metrics. We conduct proof of concepts to understand pricing before committing. Some models proved too expensive, especially for large user bases. There’s a need for tools to compare pricing across vendors, as costs can escalate quickly depending on usage.