What is Natural Language AI Training?
Natural Language AI Training is an innovative feature within Athenic AI that allows you to customize and enhance the platform's understanding of your unique data schema. Think of it as a personalized orientation session for the AI, akin to the process of onboarding a new employee to the specific jargon, metrics, and nuances of your company. By providing the AI with context about your business using everyday language, you eliminate the need for complex technical queries or SQL knowledge. This training empowers the AI to interpret your questions with a greater degree of precision, reflecting the specificities of your business operations and data schema. Athenic AI's user-friendly interface facilitates this process, enabling you to impart your business's contextual knowledge to the AI in a way that's as simple and intuitive as having a conversation.
How does Natural Language AI Training work?
Natural Language AI Training operates on the principle of contextual understanding, functioning as a reference guide for Athenic AI. You begin by compiling a list of key terms, phrases, or concepts that are pertinent to your data and business. For each entry, you provide a written explanation, much like creating entries in a customized dictionary or encyclopedia for your company. This curated knowledge base becomes the AI's go-to resource when interpreting your queries. By drawing on the context provided, the AI can deliver answers that are not only accurate but also tailored to the specific language and operational framework of your business. This process ensures that the AI's responses are congruent with your expectations and the unique characteristics of your data.
How do you use Natural Language AI Training?
From any of your Project screens, click on “AI Training'' and you simply input a key term or concept into the system, along with a clear definition or explanation. We recommend using this feature to clarify unique business terms, acronyms, proprietary formulas, or resolve any potential ambiguities within your dataset. The system is designed to automatically recognize and apply these definitions to relevant questions, ensuring that the AI's responses are consistently aligned with your business's specific context and terminology.
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Examples of Natural Language AI Training
Consider a scenario where you are using Athenic AI for customer data analysis. You might want to analyze the frequency of customer inquiries without including queries made by your own team. To achieve this, you can instruct the AI to exclude questions associated with Athenic email addresses when analyzing customer-related data. By teaching the AI this specific rule, you ensure that your analysis is focused solely on genuine customer interactions. This is just one example of how Natural Language AI Training can be leveraged to refine the AI's understanding and ensure that the insights it generates are directly relevant to your business needs.
