Robert Corwin

Oftentimes, these things are sold as panaceas where you just install this in your company, hit a button, and then it comes up with all these wonderful predictions.

That's rarely the case because at the end of the day, the devil is really in the details of this stuff.

There's no substitute for good experimental design.

There's no substitute for good data engineering and good pipelines and good coding and all this kind of stuff.

A lot of companies we've talked to have installed these seven figures or multiple seven figures on these frameworks, and they do unify things and they add a layer of abstraction.

So the whole company is kind of centralized, but they don't solve your data science problems at the end of the day by themselves.

You still need data scientists.

You still need very smart people running your analyses.

And this is where we step in.

We fill that gap.

I like to say that we come in with a SWOT team, a data science pod, if you will, of a mix of seniorities of people.

And we're very empathetic to your business.

What are your business goals?

Where are you going to save time?

Where are you going to save money?

How can we help you do that?

And we come in on a very efficient manner and just solve problems.

So contact me for the exact pricing, but let me put it this way.

What we tell clients is think of your data science problem.

Think of how many data scientists you're going to need to go hire to do that.