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How do you solve the following problems? 1. Whenever you run a natural language question the result will be the same for the same question? 2. How do you teach an agent/LLM for the datamodel of the application that stores the data in the databases?


1. By having one obvious documented way of answering the questions or accepting that humans would also come to different results.

2. Investing in good data models and documentating the edge cases. Also learning from explicit feedback is powerful.

This helps our customers at getdot.ai get highly reliable results.

The models also got a lot better at making sense of weird and complex data models in the last months.




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