Vish VarmaApr 7, 2026
Streamlining PMS Migrations with Vern 🚀
Streamlining PMS Migrations with Vern 🚀
Vish Varma·Apr 7, 2026
See how Vern simplifies PMS migrations by using AI to analyze data, resolve mapping conflicts, and clean records automatically. This demo shows how to import over 300,000 rows in minutes with reusable, self-healing migration plans.
Chapters
00:00
Introduction
Overview of the PMS migration demo using Vern.
00:10
Uploading and Analysis
00:37
Resolving Data Ambiguities
01:20
Reviewing Import Plan
01:43
Finalizing the Import
02:04
Reusable Migration Plans
02:23
Conclusion
Transcript
00:00
Hey.
00:00
Just recording a quick demo of how we're handling PMS migrations with Vern.
00:04
So in this example we have Dave's practice and Dave's coming from nucal.
00:08
And so it's really simple.
00:10
All we have to do is drop the files in here we have some exports, which contain a bunch of data relating to contacts, service fees and a patient export.
00:21
obviously the real export would have a lot more.
00:22
In this example, each of these have like a few hundred thousand rows.
00:25
So hit upload, it'll run a light data analysis on the entire files and then generate some questions to help us resolve any edge cases, ambiguities or invalid values that it detects.
00:37
and these questions are designed to be answered by you in conjunction with your customer.
00:41
So we can see here the first example is the full name column needs to be split into first name and last name as that's what your templates and your schema expects.
00:49
And so we have a few different options here.
00:51
Another example is it's asking us about the patient values include active and active and current.
00:57
How should they map?
00:59
because the destination our schema only accepts current, deleted or archived.
01:03
So we can really quickly define the mappings based on this, export we've received.
01:08
Same thing with missing values.
01:09
we know that 20% of the patients here don't have Medicare details, so we can just import them as is.
01:14
And once we answer that last question, It'll figure out how exactly we want to map the data and it'll generate a plan.
01:20
Perfect.
01:20
And we can review and tweak the plan as needed.
01:23
It'll tell us exactly what's going to be imported, what won't be imported, how the data will be organized and all of the all of the changes it will make.
01:30
So in terms of mappings, data cleaning and also issue resolution, so things like missing required fields, missing IDs, and it'll tell us exactly what we'll get.
01:41
So it looks good.
01:41
I'll hit approve and import.
01:43
And it's as simple as that.
01:44
We just wait a few minutes for all the data to be cleaned.
01:47
Perfect.
01:47
And in just four minutes we've successfully imported over 300,000 rows.
01:53
And if I click View Workbook I can really easily see that data loaded.
01:56
Perfect.
01:57
And we can see there's no validation errors and it's good to export directly into our app, as a CSV or through our webhook functionality.
02:04
What's even better is that the plan is saved for next time.
02:07
If we navigate to sources, we go to New Cal, Dave's practice has that plan saved, which can be reused for future imports.
02:15
And what's great is that it's self healing.
02:17
So every time a new change is introduced or there's a new edge case, the AI will intelligently adapt the script.
02:23
If you're keen to see this on, a real data set, shoot me a message and we'll get you set up within a week.
02:28
Cheers.