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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? 🧵
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 🧵
My Chief of Staff is leaving to start her own company, so I'm hiring!. Looking for someone who founded a company or was early at one that scaled to tens of millions in revenue. Reports to me. NYC, in office 3x/week.
jobs.ashbyhq.com/middesk/0a7…
I've been lucky to partner with @stephzhan for the last six years.
She's been demanding and supportive, helping us to push the business from the first iteration of the product to the thousandth customer.
Excited for what's next for you!
I’m starting a new early-stage AI fund, doing what I love: partnering with founders from company formation on bold bets, long before consensus.
The fund’s LPs will include Sequoia, Jeff Dean, Sachin Katti, Philip Wong (my Stanford professor and Chief Scientist adviser to TSMC), and others whose work has shaped our industry and how I think about AI’s future.
I’ll remain a partner at Sequoia and keep serving on my boards on Sequoia’s behalf.
Sequoia has been my home for the past 11 years. I joined as the youngest investor the firm had ever hired. I grew up here. Through years of intense debate and shared work, I found lifelong mentors and friends who took me under their wing and taught me this craft. They taught me to aim high and take big swings. I’ll carry that into what I build: outsized ambition, relentless truth-seeking and curiosity, and a refusal to become complacent.
Working alongside founders has made me want to build something of my own: a firm shaped from day one around the convictions I’ve developed over the past decade.
Life has taught me not to take time for granted. This is how I want to spend mine.
Why now
We’re seeing a new way of building companies in today’s AI era. Research and products often advance together. A breakthrough can open a market or accelerate a business far faster than expected. Some companies require extraordinary capital and compute early on. Others reach meaningful scale with remarkably small teams. The rules for how big these businesses can get, and how fast, are being rewritten.
But early on, the technology is unproven, the resources required enormous, and the vision seemingly implausible.
This is what I love most: seeing the potential right from the beginning, and helping founders realize their full scale of ambition.
More than ever, it starts with an extreme willingness to believe early, with bold, independent conviction in a founder’s technical insight before any product or market validation. Then, it means helping founders take the biggest swings, giving the rare, long-term patience to see those bets through uncertainty, ambiguity, and turbulence, and serving as a level head when the stakes are highest.
I learned this kind of partnership at Sequoia. It’s the foundation of the firm I’m building.
Believing before consensus
My fascination with AI’s potential took root at Stanford in the early-to-mid 2010s, studying computer science and working in Andrew Ng’s lab. The friendships I formed connected me to a community whose people and ideas would help shape modern AI and build some of our generation’s defining companies. What stayed with me was the gap between what those people saw was possible and what the wider world could imagine.
I’m drawn to founders pursuing ambitions that sound impossible today.
I start with a simple question: “What if everything goes right?”
Then we work backward together to make it happen.
In 2023, Deepak and Abhinav set out to build a general-purpose robot brain at @SkildAI, before physical AI was a consensus bet. Their sim-to-real breakthroughs gave me conviction where earlier robotics approaches had fallen short. But the data flywheel required deployment at scale. We made commercialization as urgent as research and brought in strategic partners like NVIDIA and SoftBank to support the ambition. Three years in, Skild is advancing the frontier of physical AI with nine figures in annualized revenue.
In 2024, Ioannis and Misha founded @reflection_ai with an insight into scaling reinforcement learning. As that grew into the ambition to build a Western frontier lab for open models, the hard question was how a startup competes with labs spending tens of billions. An introduction to NVIDIA and many compute calls and recruiting events later, the team has built Beam, now one of the leading US open models.
In 2025, Anna and Azalia, the co-creators of AlphaChip, founded @RicursiveAI to design models and hardware together. From day one, we made early customers and ecosystem partners a priority. Today, they are showing order-of-magnitude improvements on real workloads, working with some of the industry’s most consequential players, and reaching a defining inflection point.
The ambition keeps growing as these companies scale.
@linear has always had a kind of magic to it. Now it’s the system a new generation of AI companies builds on, for teams and agents alike.
@tavus saw early that we’d one day talk to AI the way we talk to each other. Today, it’s building the human computing interface for a world of AI colleagues.
@Mach_Industries began as hydrogen experiments in an MIT dorm room. It has since become one of the most exciting next-generation defense companies.
Making the ambition possible
Being a first believer is only the beginning. Compute falls through. A deep-pocketed incumbent makes your mission its top priority. A breakthrough changes the opportunity and the capital required overnight.
These are stomach-churning moments, and early belief carries a responsibility to help make the bet work.
This is the partnership I love: turning the full ambition into concrete steps. Raising capital, securing compute and strategic partners, recruiting exceptional people, and winning the first customers together. Thinking several moves ahead while solving what’s in front of us. And as breakthroughs open new possibilities, helping founders dream even bigger.
Thank you
To the founders I’ve worked with: thank you for trusting me and Sequoia to be your first partner and first believer. It’s been the joy of a lifetime, and I can’t wait to keep building together.
Thank you to Alfred and Pat for your leadership of Sequoia and your support of my next chapter. To Roelof, for bringing me into Sequoia and believing in me from the beginning. Alfred and Roelof, you have been mentors in investing and in life. So much of what I know, and the investor I’ve become, comes from your guidance and generosity over the years. To Bill, for the close partnership and wealth of knowledge, always wrapped in humility. To Shaun, for showing me how to think deeply and imaginatively. To Michael Moritz, for inspiring 22-year-old me to dream big. To Doug, for teaching me to keep things simple. To Bogie and Jess, for bringing joy to the everyday and perspective on what matters. And to all my Sequoia teammates, for the friendship, camaraderie, and lessons I’ll carry with me.
To my family, especially my husband and my brother, who have each started companies of their own: thank you for giving me the courage to take this leap.
Let’s get to work!
New fraud pattern we're seeing: fraudster finds real companies formed 2-3 years ago with no website, vibe codes websites for all of them, applies across the same 6 Middesk customers within a a few hour period.
Currently tracking ~70 companies being used to apply for banking and card products that fit this same fingerprint.
In some cases, the business owner is finding out, but not always. In one example dissolved their entity and left a note "IDENTITY FRAUD, SOMEONE TRIED TO OPEN ACCOUNTS USING OUR LLC" on the dissolution paperwork.
If you want a list of the company names being used to open these fraudulent accounts, DM me or reply in comments.
Also if you want to learn more about these patterns, come to our event Stratos on 9/22 in Brooklyn. You can register here: bit.ly/4xtOvo8
FinCEN just removed the closest thing the U.S. had to a federal source of truth for business ownership.
15M+ BOI reports for U.S. businesses are being thrown out. ~27.5M businesses that were expected to file now never will, meaning their ownership data will never be collected.
The most interesting part of the BOI rollback isn’t that 30M+ businesses no longer have to report their owners.
It’s the bet behind the policy: collecting beneficial ownership information from every legitimate business costs more than the value it creates in finding the bad ones.
That may be the right tradeoff.
But it puts a much higher bar on the systems we use to identify the businesses that actually warrant scrutiny.
Read more: bit.ly/4xHcdwW
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I'm looking for someone to run growth at Middesk. We’re growing a lot and I need this person to use that momentum to push harder.
You'll own growth end to end, reporting straight to me; no layers, no red tape. DM me if this is you:
You have good instinct; you know what's working, what to kill, and what deserves dropping everything to double down on.
You’re creative and like to experiment.
You get shit done.
You spend too much time on X.
No resume needed - send me the best idea you've had OR the weirdest thing you've shipped that worked, and your LinkedIn profile.
If you refer someone we hire (or if this person is you), we’ll send you $5k.
DM me or email kyle@middesk.com
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Middesk 🤝 Docusign
Middesk is now in the @Docusign App Center.
Verify the business behind every agreement before anyone signs, inside the workflow you already use.
One workflow. Verification, agreement, signature.
tinyurl.com/3j6zacwt
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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/kxnycorp/…
Middesk just hit 70,000 all-time businesses registered for state tax accounts.
Q1 2026 is +180% Y/Y.
Behind every great yes is the new @MiddeskHQ
middesk.com/blog/the-new-era…
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Had a great chat with @ReggieCYoung about all things business identity, AI, and the future of @MiddeskHQ
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 roughly 400 government agencies across the U.S. to bring primary-source business data into onboarding and risk workflows. Without complete, reliable data, it's difficult to distinguish a fraudulent entity from a legitimate company that incorporated three days ago. And impossible to automate decisions with confidence.
That layer has to be right before anything else can scale.
buzzsprout.com/1985266/episo…
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TLDR we mapped $1.7B in Medicaid payments to high confidence fraud
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 🧵
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 🧵
Great agents need great data. We built both.
For six years, we built the most reliable foundation for business verification.
Today, we're using it to power the next era of business identity - intelligence.
Middesk agents don't just surface signals, they investigate them automatically. They acquire data, synthesize findings, reason across complexity, and deliver decisions - not alerts.
The compliance queue doesn't need more headcount. It needs infrastructure that thinks.
Introducing Middesk Agents. Business identity that runs itself.
Read about it here: na2.hubs.ly/H03NCH80
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2025 @MiddeskHQ
- 10% of all companies formed in the United States are verified by Middesk within 90 days of formation
- 5% of all state payroll tax accounts in the United States are created by Middesk
- Added 125 data sources (>400 now available today across federal, state, local) with average data refresh of ~7 days
- 18% increase in auto-approval rate across all customers
- 127% NDR
- >600 customers now use Middesk with global businesses like Comcast, Wex, Stallantis joining the last in December
Our top priorities for 2026:
1. Grow core KYB business, launch automated KYB in new jurisdictions
2. Expand intelligence layer via graph insights, predictive fraud models, and agents
3. Broaden reach of embedded business registration products within and outside of payroll
Along the way we will continue to expand our data acquisition, improve data freshness, decrease turnaround times, iterate on our dashboard experience, improve developer tooling and docs, and make sure we have best-in-class uptime.
Anything else that you’d like to see from Middesk in 2026?
In the early day of @MiddeskHQ, the entire founding team learned the role of a risk and compliance analyst.
Our customers rely on us for trusted data to automate onboarding decisions, so to ensure that every result was accurate, we decided we that we would create an operational review flow for every condition where quality could be an issue.
But onboarding happens 24 hours a day, 7 days a week.
On any given night at 3am, you could find one of us manually reviewing businesses, digging through state filings, cross-referencing addresses, and tracing ownership chains.
But doing that work taught about each edge case, how information gaps cause delays, which patterns matter for risk assessment, how expert analysts actually reason through decisions. For the last several years, we've offered an "Analyst in the Loop" service to our customers, where we become an extension of their team, helping them resolve edge cases.
Now, we're excited to 10x that strategy and transition the model from Analyst in the Loop to Agent in the Loop -- enterprise-grade, specialized AI agents that draw on the tens of thousands of hours of in-house expertise and reviews to accelerate the investigations, intelligence gathering, and synthesis of business data.
These agents can handle basic cases like discovering additional context on where businesses operate, to complex cases like exploring our internal identity graph of every registered company in the United States to derive signatory authority of complex entity structures.
We're actively launching our first agents now, and have a extensive list of specialized agents to follow. These are available via our dashboard and we have an A2A protocol for our customers or partners to leverage to incorporate our specialist agents into their own platforms or agentic workflows.
Like everyone else, I’ve been spending the weekend reading all about this alleged Minnesota fraud and wanted to use the tools that we have at @MiddeskHQ to see what we could learn.
Verifying a business is a challenge but not an unsolved problem. There is a difference between a business that is real on paper (i.e. they have registered with the Secretary of State) and one that has legitimate business operations.
This evaluation is contextual, so you wouldn’t automatically decide that a business that has only formed last week and doesn't have a credible office location is illegitimate. When we started Middesk, we didn’t really have a business for at least 6 months and were running the company out of my apartment.
But there are signals that we can look at to build a more complete picture of a company, even if they are just getting their business off the ground.
I pulled 2,000 child care and home health care companies formed in Minnesota with a registered operating address in Minneapolis. To build the list, I focused on companies that mentioned child care or home care in their entity name to expand the scope beyond what we might have found if we only looked at industry specific licenses.
I placed the businesses on a graph to show the relationships, which looked like this:
Then I looked at clusters of businesses that were using the same or similar addresses as their operating location.
You can see the heatmap of address density below, but consider that a single block in MN has more than 100 companies from the sample of businesses that we used for this dive.
We can also see some of the businesses visited in the @nickshirleyy video within that block, along with other high density blocks.
Next, I looked at the connections between companies, since businesses are easy to shut down and re-open on paper. Connections were based on shared addresses, individuals, and ownership structures.
For example consider this cluster of related businesses:
12 companies connected through 3 shared addresses and a shared officer. 2 of the companies in this cluster are visited in the video. These businesses are the red ones.
And TBC, it doesn't mean that all businesses in the cluster are fraudulent, just an example of higher risk.
To go a bit further, I looked at the online web presence of the entities in the cluster above and found that of the 12 companies, all have no credible online web presence (Google Places page, recent reviews, online/available website, etc.).
When you consider that the average age of these 12 businesses is 8 years, this increases the risk of the cluster further. You would expect businesses formed in the last 8 years to have some meaningful online presence.
Next step would be expanding beyond Minneapolis and layering in funding data like grants, PPP loans, etc. But the clustering patterns alone tell you a lot.
We built @MiddeskHQ for our customers. Now we’re building for their agents too. Middesk MCP and GraphQL API is now available! More here hubs.ly/Q03X5k370
Thanks @meetgranola for a potential new vision statement for @MiddeskHQ
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