Let us take a closer look a how ThanoSQL enables interactive style analysis using the scenario below.

The image below shows the initial screen of the ThanoSQL workspace. To begin analysis,
select the table where the target data is stored, then enter your question in the input field.

In this example, customer reviews must be analyzed first, so the customer_review table is selected. Next, the product_list table is chosen to identify the product, followed by the sales table to check the sales volume.

The natural language query is automatically converted into SQL commands executed on the selected tables, incorporating various AI algorithms and machine learning techniques. ThanoSQL provides these algorithms and models by default, but users can also import external models from platforms like Hugging Face.

The results are then presented in natural language format in the output field.

With only a few natural language inputs, users can analyze unstructured data, such as customer reviews, alongside structured data, like sales figures, and view results instantly.

In short, ThanoSQL is an analytical tool that allows users to perform interactive analysis on both structured and unstructured data stored in database tables by combining machine learning with LLM.

Therefore, as shown in the example above, ThanoSQL allows users to quickly analyze organizational data and uncover meaningful insights without specialized IT knowledge.