Today we took a look at how RIDL maps data to HubSpot objects.

We are in the phase of understanding how well it does it’s job as an agentic AI RevOps rep.

From loading the data to mapping less than a minute.

We can still use drop downs.

We tools like Zapier, Make, n8n, and Syncari and they are great tools.

I have think though wouldn’t it be better if the computers could just figure out how to talk to one another?

Call me a dreamer but I kinda love that C3PO can speak a quadruple zillion languages.

So instead of making me figure it out… RIDL is doing that job.

Is it always perfect? Oh hell no.

Is it usually good enough? Yep.

Humans screw this up all the time too.

Especially when it novel data.

In the context of artificial intelligence and machine learning, novel data refers to new, previously unseen, or unknown data that differs in some way from the data a model was originally trained on. The significance of novel data varies depending on the specific machine learning task, and it is a central concept in techniques like novelty detection and zero-shot learning.

So RIDL is doing a pretty good job of creating the base HubSpot objects right now and it’ll only get better the more data we pass through it.

Now if only the migration to HubSpot was fully fuctional.

Tomorrow… tomorrow. Mwhahahaha.