Curious if AI startups develop proprietary models or simply leverage external APIs. How do they manage API costs while supporting non-LLM functionalities like prediction and text extraction?
i think many ai starups adopta hybrid approach using external apis for common tasks, while developing their own unique modelos for niche function. helps balance costs and innovation.
Based on my experience monitoring and advising early-phase companies, many startups initially lean on third-party APIs to cover fundamental tasks such as prediction and extraction since it allows them to focus more resources on customer acquisition and core product innovation. However, as their needs become more specialized, some choose to invest in developing proprietary models. This approach typically evolves over time, with a shift occurring when the potential gain in performance and market differentiation justifies the additional expense and development effort.