Master Salesforce AI Specialist Exam 2025 – Dive Into the Future of Innovation!

Configuring a custom generative model for a troubleshooting chatbot is essential when there's a need for specific terminology recognition. This situation often arises in technical or niche fields where standard models may not adequately understand or appropriately respond using the unique vocabulary and jargon relevant to the industry. By customizing the model, the startup can ensure that the chatbot accurately recognizes and utilizes the specific terms, acronyms, and phrases that users expect, enhancing the overall user experience and improving the quality of interactions.

In contrast, for basic customer inquiries without technical depth or when the dataset is limited and no customization needs are identified, leveraging general models may be more than sufficient. Using a model trained on general technical documents also lacks the nuanced understanding that a custom model can provide, especially in scenarios where precise terminology is crucial for effective troubleshooting.