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Tech Brew Ride Home

(Portfolio Profile) Automated Data (Corrected)

Tech Brew Ride Home

Amalgamated Internets, LLC

Tech News, News, Technology

4.71K Ratings

🗓️ 13 November 2023

⏱️ 57 minutes

🧾️ Download transcript

Summary

Our first Ride Home AI Fund Portfolio Profile Episode: Automated Data Learn more about your ad choices. Visit megaphone.fm/adchoices

Transcript

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0:00.0

Welcome to another weekend bonus episode of the Tech Mem Right Home, another portfolio profile episode.

0:12.0

Actually, this will be the first portfolio profile

0:16.1

episode to feature a company that the Ride Home AI Fund has invested in, although as listeners know both funds invest in the AI companies

0:28.3

as well.

0:29.3

But today we're going to talk to automated data or ADI, depending on how we're going to call it in this conversation.

0:39.0

We're going to be talking to two founders, Michael and Jason Michael first hello to you.

0:46.6

Hello hello thanks for having us.

0:48.2

Jason or should I say J. T.

0:51.1

Either one's fine I guess it might depend on whether you're angry at me or not.

0:55.0

Well, let's start off with sort of what ADI does. I should say up front that if people want to learn more as we're talking,

1:06.2

the website is automated dash data.io. But whoever wants to do it, give me sort of like the two minute elevator pitch

1:16.1

about what y'all are building.

1:19.3

Yeah, I can certainly start this mic.

1:21.7

And then JT loves to and does a much better job of

1:25.1

completing my sentences so why don't we take that approach so automated data is

1:30.3

essentially building out a data matching platform.

1:38.3

Our goal is to materially automate

1:40.6

the matching of data,

1:41.5

which is arguably the most complex part of a data

1:44.0

integration task right and what what we like to tell people is we're trying to

1:49.3

bring the data citizen and empower them with the tools that enables them to match data in the same way that a very seasoned and senior data engineers doing or even a data scientist for that matter.

2:01.0

And the reason we're doing this is because number one it's really

...

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