Tag: Andreessen Horowitz

Prince Mario-Max Schaumburg-Lippe: Armadin Raises $255.5M at $2.5B for Agentic AI Security

There is a particular kind of founder who only needs a name. Kevin Mandia is one of them. The man who built Mandiant into the firm governments called when things went badly, and who sold it to Google, has a new company. And investors just handed it a quarter of a billion dollars to teach AI to think like a hacker, in defense of the good guys.

Armadin announced on October 1 that it has raised $255.5 million in Series B funding at a valuation of more than $2.5 billion. The round was co-led by Andreessen Horowitz and Accel, with new money from Bain Capital Ventures and Redpoint, plus a deep bench of returning backers: Google Ventures, Kleiner Perkins, Menlo Ventures, In-Q-Tel, 8VC, and Ballistic Ventures. Total funding now sits at $445 million, for a company that only emerged from stealth seven months ago.

The core idea: fight AI with AI

Let’s be honest about the problem first, because it’s the kind of thing that usually gets framed with doom. Frontier AI models have compressed the time between a vulnerability being disclosed and a working exploit appearing. What used to take attackers weeks can now take hours. The old defenses, a penetration test twice a year and a scanner that spits out a list of findings, were built for a slower world.

Armadin’s answer is an inversion that feels obvious once you hear it: deploy an autonomous swarm of specialized AI agents that reason like a skilled adversary. Not a scanner that flags individual issues in isolation, but agents that chain individually low-severity weaknesses into full, validated attack paths. The company’s description of a kill chain is worth quoting in plain terms: it can run from unauthenticated remote code execution at the perimeter, through lateral movement inside the network, to full cloud compromise. The point is the chain, not the links. Scanners score each finding on its own and miss how they connect. Attackers don’t.

This is the part that should make security teams sit up. Armadin says security teams get to see the exact attack paths an adversary would use in production, with the blast radius of each mapped out, and can cut those paths before anyone exploits them. In other words: you get to watch the heist in rehearsal and lock the doors it would have used.

Why this raise matters right now

Two things make the timing notable. First, seven months after emerging from stealth, the company says it’s already running agentic attack campaigns in production for Fortune 500 enterprises and government customers. That is a very fast path from stealth to production, and it suggests the demand side is urgent. Enterprises aren’t buying a vision here; they’re buying capacity.

Second, the money flooding into AI-native defense is becoming one of the defining investment themes of 2026. Investors have been pouring capital into early-stage startups building protections against AI-driven cyberattacks all year. A $255.5 million Series B at a $2.5B-plus valuation is among the largest raises the category has ever seen, and the investor list reads like a vote of confidence in both the founder and the thesis.

Mandia’s pedigree is doing real work here. He has sold a security company to Google before, and he has been on the receiving end of the nastiest incident-response calls in the industry. When he says periodic testing can’t keep pace anymore, it lands differently than when a first-time founder says it. The track record is the pitch.

The “good-guy red team” model

Zoom out and Armadin represents a structural shift in how security gets bought. The traditional model is expertise-as-a-service: hire a red team for a few weeks, get a report, fix what you can, repeat next year. It’s episodic, expensive, and the attackers don’t take semesters off.

The agentic model is expertise-as-software: the adversary simulation never stops. The swarm keeps probing, keeps chaining findings, keeps updating the map of how an attacker would actually get in. For a Fortune 500 company with cloud estates that change daily, continuous is the only honest answer. Your infrastructure doesn’t pause between pen tests. Why should your testing?

There is a nuance worth holding onto. These systems are powerful, and power in security tooling always raises the dual-use question. But the framing here is firmly defensive: the agents find the paths, the security team closes them. The company exists to make the defense faster than the offense. In a year when AI safety has been a constant drumbeat, a well-capitalized defense-first company is good news for everyone who isn’t an attacker.

What to watch next

Three things will determine whether this raise is remembered as a landmark or just a big number.

Proof of production value. The Fortune 500 claim is the one to watch. If Armadin can show that continuous agentic testing measurably shrinks the window of exposure, competitors will have to match the model, and the whole pen-testing industry reorganizes around it.

The talent magnet effect. $445 million in total funding, a Mandia-led company, and a mission that reads like a spy novel: this is a recruiting machine. In a security talent market that has been brutally tight for years, that matters. The best defenders are going where the hardest problems are.

Pricing the defense premium. Right now, agentic security is enterprise-only by economics. The question is how fast the model gets cheap enough for the mid-market companies that are actually the softest targets. The sooner that happens, the bigger the dent in the attack economy.

The takeaway

Strip away the funding theatrics and the story is simple. The same AI advances that made attacks faster are now being aimed at defense, by one of the most credible security founders alive, with a quarter-billion dollars of fresh fuel. The attackers have had the momentum. This is the market voting, loudly, that the defenders are catching up.

If you’re in New York this week and security talk over dinner sounds fun (it is, trust me), there’s a full lineup of things to do across the city to pair with the conversation. And if the funding news has you dreaming of your own security startup, fuel up properly first: NYC’s best breakfast sandwiches are a fine place to sketch a pitch deck.

Prince Mario-Max Schaumburg-Lippe: EliseAI Hits $4B Valuation With $350M AI Raise

While the AI industry argues about whether we’re in a bubble, one company just posted the kind of numbers that end arguments.

EliseAI announced Tuesday that it raised $350 million in a round led by Andreessen Horowitz and Bessemer Venture Partners, with participation from the Ontario Teachers’ Pension Plan, Sapphire Ventures, and Navitas Capital. The valuation: $4 billion. That’s nearly double the $2.2 billion valuation from its Series E round in 2025.

But the number that actually matters came one sentence later. The company surpassed $200 million in annual recurring revenue in June — and it has doubled revenue year over year for the fifth consecutive year. Five doublings. In a row.

What EliseAI actually does

Forget chatbots. EliseAI sells automation to the two most paperwork-burdened industries in America: housing and healthcare.

For property managers, its platform automates leasing, maintenance requests, and lease renewals — the endless churn of tenant emails, showing schedules, work orders, and follow-ups. For healthcare, it works with physician groups on patient intake, scheduling, insurance checks, referrals, and follow-up coordination. If you’ve ever sat on hold with a doctor’s office trying to reschedule, you’ve experienced the exact problem EliseAI is selling the fix for.

The new funds go toward expanding engineering, deployment, and sales, and toward establishing San Francisco as a second engineering hub alongside its New York headquarters.

The timing lines up with the demand data. Bank of America Institute reported that AI spending growth among mid-sized firms peaked in August, concentrated specifically in healthcare and education admin automation. EliseAI isn’t chasing a trend. The trend is chasing EliseAI.

The money is in paperwork

Here’s the thesis that keeps winning in enterprise AI: pick a painful workflow, own it end to end, charge real money for it.

Consumer AI gets the headlines — the demos, the viral launches, the existential debates. But the revenue is in the unglamorous stuff: the leasing office drowning in maintenance tickets, the medical practice where front-desk staff spend their days on insurance verification calls. Nobody posts about those workflows on social media. Everyone pays to fix them.

EliseAI’s approach is the opposite of the general-purpose assistant. It doesn’t try to be useful at everything. It buries itself in one domain — property management, medical intake — until it knows the forms, the edge cases, the compliance requirements better than the humans currently doing the work. That’s what “vertical AI” means in practice: narrow scope, deep competence, and a product that slots into an existing operation instead of asking the customer to reinvent one.

The fifth consecutive revenue doubling is the detail the “AI is all hype” crowd can’t easily wave away. Hype doesn’t double revenue five times. Contracts do. The company’s customers are paying — and renewing — because the automation works well enough to justify the invoice. That’s the oldest signal in business, and it still works.

Why vertical keeps beating horizontal

Look at the broader enterprise AI market and a pattern emerges. The companies winning real contracts are the ones that arrive with domain expertise baked in. Healthcare AI has to know how insurance verification actually works, including the maddening variations between payers. Proptech AI has to know what a lease renewal workflow looks like at 2 a.m. when a tenant’s heater dies.

A general model can’t learn that from the internet. It has to be built, workflow by workflow, customer by customer. That’s slower and less exciting than launching a consumer app — which is exactly why the moats are deeper. Once EliseAI’s system handles a property manager’s entire leasing pipeline, switching vendors means ripping out the nervous system of the business. That’s a very sticky $200 million in ARR.

Contrast that with the horizontal players fighting over who has the best general chatbot. Lower switching costs, murkier pricing power, constant feature races. Useful? Sure. But the enterprise buyers with actual budgets are voting for the company that eliminates their phone tag.

The physical-world connection

There’s a wider thread worth pulling. The most durable AI businesses of this cycle are the ones touching the physical world — the scheduling, the maintenance, the intake desks, the front lines where digital systems meet real operations. We see the same pattern in autonomy: driverless trucks moving onto public roads, robot fleets scaling in Texas, robots taking on warehouse work. The AI that matters economically isn’t the AI that writes poetry. It’s the AI that handles the work nobody wants to do.

EliseAI understood that earlier than most. Five doublings later, the market is catching up.

The takeaway

Bubbles are characterized by rising valuations and flat revenue. EliseAI has rising valuations and revenue that has doubled five years running. Andreessen Horowitz and Bessemer don’t write $350 million checks for vibes; they write them for $200 million in recurring revenue with a growth curve that looks like a staircase.

The lesson for founders is unfashionable but clear: the biggest AI opportunity isn’t the flashiest model. It’s the most annoying paperwork. Find the industry where skilled humans are still doing robotic work, and build the robot.