Using ChatGPT for backend services in SaaS platforms presents significant challenges, primarily concerning performance and cost-effectiveness, as API calls introduce notable latency and recurring expenses that can quickly escalate with increased usage. A major hurdle is maintaining reliability and deterministic behavior, given the inherent variability of LLM outputs, which can compromise critical backend logic requiring precise and consistent responses. Data privacy and security are paramount concerns, as sending sensitive user information to a third-party service raises complex compliance issues like GDPR or HIPAA and potential data leakage risks. Furthermore, managing API rate limits, robust error handling, and unforeseen downtime from the external service adds considerable operational complexity. Finally, coping with frequent model updates and versioning demands continuous integration adjustments, posing a risk to application stability and long-term maintenance. More details: https://www.pearlevision.com/m20ScheduleExamView?storeNumber=21129027&clearExams=1&catalogId=15951&langId=-1&storeId=12002&returnUrl=https://www.abcname.com.ua