Kyle Mack @KyleTMack

CEO of @MiddeskHQ New York, NY Joined August 2013

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192
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1K
Following

314
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781

Kyle Mack @KyleTMack

2 days ago

Is @NYCMayor good or bad for business? New York business formations just hit an all-time high in March. Every policy out of City Hall now moves a live market, and you can trade it on @Kalshi. Kalshi chose @MiddeskHQ as its official real-time settlement source for business formation. We’ll be keeping a real-time read on the state of the business economy. kalshi.com/markets/kxnyco…

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Kyle Mack @KyleTMack

a month ago

Middesk just hit 70,000 all-time businesses registered for state tax accounts. Q1 2026 is +180% Y/Y.

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Kyle Mack @KyleTMack

3 months ago

Behind every great yes is the new @MiddeskHQ middesk.com/blog/the-new-e…

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Kyle Mack @KyleTMack

4 months ago

Had a great chat with @ReggieCYoung about all things business identity, AI, and the future of @MiddeskHQ

Middesk @MiddeskHQ

4 months ago

AI models aren't the constraint for business identity. Business data is. Middesk CEO Kyle Mack joined Reggie Young on Fintech Layer Cake (presented by Lithic) to talk about why automation in fintech depends on the quality of the identity layer beneath it. Middesk works with

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Kyle Mack @KyleTMack

4 months ago

@typesfast What do you think will be the ways fraud will happen through the broader refund process?

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Kyle Mack @KyleTMack

4 months ago

@imthemusic This is only one narrowly defined fraud pattern related to paying out to blacklisted providers

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Kyle Mack @KyleTMack

4 months ago

@DOGE_HHS @MiddeskHQ 300K+ views later, people are asking: what does this fraud actually look like up close? x.com/KyleTMack/stat…

Kyle Mack @KyleTMack

4 months ago

Yesterday we posted what @MiddeskHQ found when we cross-referenced the @DOGE_HHS dataset against our business identity infrastructure. 300K+ views later, people are asking: what does this fraud actually look like up close? 🧵

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Kyle Mack @KyleTMack

4 months ago

HHS just open-sourced the largest Medicaid dataset in history. About $1T in claims data, free for anyone to analyze via @DOGE_HHS. Everyone's looking at what was billed. At @MiddeskHQ, we're looking at who's behind the billing. Here's what we found 🧵

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Kyle Mack @KyleTMack

4 months ago

@dpatil @bgurley Couldn’t agree more

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Kyle Mack @KyleTMack

4 months ago

At @MiddeskHQ we do this every day for banks and fintechs. The same tools can protect public programs. DM me or reach out at [email protected]

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Kyle Mack @KyleTMack

4 months ago

This is one cluster. Across our analysis, we found networks of providers totaling $1.7B in Medicaid payouts linked through shared addresses, officers, and formation patterns. The truth is mapping these connections is difficult, it requires broad data access, tooling, and strong analytical research.

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Kyle Mack @KyleTMack

4 months ago

Kyle Mack @KyleTMack

4 months ago

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Kyle Mack @KyleTMack

4 months ago

@inferencepoint @DOGE_HHS @MiddeskHQ 100% the dive you did is great. Excited to keep following the rabbit hole!

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Kyle Mack @KyleTMack

4 months ago

@bgurley Engineers in HHS like @zachterrell57, @nixonandrewg spoke with Axios on making the data public, obviously @elonmusk amplifying and helping to make this possible.