I mean as an answer to the questions: for example, give me the average sales by region in a chart, and we get a chart with the data.

Great news. Also can you please add some opensource libraries for correlation, clustering and regression?

So when it comes to this does this mean we will be able to customize dashboards/workspaces with Pies, Funnels, Radar, Donuts,Scatter/Bubble plots, etc... And will there be potential for drag and drop functionality (then connect mapping)?

@BMiglionico

Q:we will be able to customize dashboards/workspaces with Pies, Funnels, Radar, Donuts,Scatter/Bubble plots, etc...
A: Yes

Q: And will there be potential for drag and drop functionality (then connect mapping)?
A: Please describe your vision for the drag-and-drop functionality. Currently, you need to tell the AI about what you need.

@teycir
Q: can you please add some opensource libraries for correlation, clustering and regression?
A: Can we chat? I'd love to learn about your use case.
https://calendly.com/conduitapp/

@Max,

Apologies as I re-read and see I didn't fully explain my case use scenario.

What I mean is lets say I Whitelabel, and embed via Iframe a workspace into my custom CRM for a client. And they want to track let say 7 specific medium (ie; Facebook Ads, Tik-tok, Linked-In, etc...) will we be able to design an dashboard of sorts via a potential drag and drop process. Say I want 1 row- 3 columns- 1st column/widget is a Pie-Chart, next column/widget a Bar Graph, then a plot chart, etc... etc... Do you design the aesthetic look and feel, and click each widget to connect the sources to display in each widget.

I hope that makes sense, unfortunately I can't attach a screen shot for visual purposes...

@ Max: thanks for the reply, my use case it to do data analysis. Imagine ChatGpt Code Interpreter + your workflow feature. Concerning the open source librairies, you can integrate those used by Python. Example: First, when your application starts, you could load your scikit-learn model into memory. This could look something like this in Python:

```python
from sklearn.externals import joblib
model = joblib.load('your_model.pkl')
```

@BMiglionico

Yes, you can design a layout at the top level, though there are some restrictions. See below.

You can create rows and link each to a single data source, a row is limited to connecting with just one data source. Therefore, if you aim to design a row with three columns, where each column contains a widget pulling data from different data sources, you cannot achieve this directly.

Instead, you can implement an additional step—create a workflow that consolidates multiple data sources into a single dataset, where each column aggregates data from various advertising platforms.

With this setup, you can then configure a row using the workflow as the data source and create widgets (columns) that represent different data sources.