• Mave has raised $34 million to bring AI agents to companies' security operations.
• CEO Raziel Oren said old systems can't keep up with how quickly AI is transforming cyberattacks.
• Business Insider got an exclusive look at the pitch deck Mave used to raise its Series A round.

Mave, a cybersecurity startup that uses agents to counter the rise in AI-powered cyberattacks, has raised $34 million in funding.

The Israel-based startup says its AI agents pull together information from a company's existing security systems, investigate alerts, filter out false alarms, and take actions approved by human teams.

"Security operations is the last gate in any organization," cofounder and CEO Raziel Oren said, comparing it to the physical security guards who monitor a building's live camera footage. "This thing is really broken from the inside. The roots of the solutions there are just not keeping the relevant pace with the emerging threats."

AI has transformed cyber threats at a dizzying pace. Attacks can happen much faster and on a much larger scale, and Oren predicted that the increase in agent-powered incidents will be "exponential."

Mave says its own agents help human security teams keep up. "You can't hire your way out of this," Oren told Business Insider. "There must be a change in how you do [security operations] in order to protect your organizations."

Oren cofounded Mave with Guy Eshel in 2025 after years of friendship. The two met when Oren was Eshel's mentor in unit 8200 of the Israel Defense Forces, which sits under the intelligence corps and gave them firsthand experience with cybersecurity issues.

AI agents have come under the spotlight after a string of high-profile security breaches. Corporate leaders have grown increasingly worried about the cybersecurity risks AI poses, and some of Wall Street's executives spent third-quarter earnings calls explaining how they're defending against rogue AI agents.

The technology has also been used by researchers to uncover security flaws: this week, OpenAI said one of its AI models had helped identify a vulnerability that puts 70% of the world's websites at risk.

Oren said it takes some customers time to become comfortable handing over security operations to agents, but that the product's transparency is key to building trust. Mave says its agents track each step of their thousands of workflows, giving human employees insight into the agents' reasoning and actions.

Mave charges its customers a flat rate, depending on the company's size and needs. Other startups have also jumped at the opportunity Mave sees, including agentic cybersecurity companies Dropzone and Prophet Security.

Mave's $34 million funding consists of $28 million from a recent Series A round, led by Red Dot Capital Partners and with participation from Lumir Growth Partners, and an earlier $6 million seed round.

The startup currently has 30 employees and plans to use some of the fresh capital to continue expanding the team, mainly for go-to-market roles and AI research.

Read the pitch deck Mave used to raise its Series A round:

The co-founders met in the army.

Cyberattacks are happening much faster.

Mave consolidates security operations.

In one instance, Mave says it stopped ShinyHunters, a cybercriminal group.

Customers include Fortune 200 and Fortune 500 companies.

• I tested out the leading AI agents for a while, and gave them each the same tasks.
• OpenAI's Dot saved me from failing to file my taxes, but was the worst at ordering lunch.
• Ultimately, dealing with multiple AI agents at once is a hassle!

I've been playing around with various AI agents — Muse, Instinct, and OpenAI's Dot, and I've found them genuinely really useful for certain things.

But which one is best?

I put them to some, uh, semi-rigorous testing. Ok, not totally rigorous or controlled, but I gave them all the same 3 tasks — triage my email, order me lunch, and build me a personal website — and it was interesting to see which worked best. It was also interesting to see how differently they functioned at these tasks.

If you haven't started using an AI agent yet but are curious, well, I'm not sure that this is going to answer all your questions, but maybe is a place to get started.

A big spoiler here for my ultimate recommendation: right now, Meta's Muse is the only free one of the bunch, so in my mind, that wins for most normal people who just want to try an agent out. OpenAI's Dot is only for the $100/month plan (ouch!) and Instinct is currently invite-only.

To me, that's a no brainer. Do the free one (unless you're already paying for the ChatGPT plan, in which case you're probably already a pretty pro user and probably don't need my advice).

Challenge #1: Manage my email

I get a lot of email. Most of it I don't need to bother opening. Help me figure out which are the important ones.

Muse: Muse has been a dutiful soldier here, and this was pretty much the first task I gave it when I started using it a few weeks ago. So far, "triage my email" has been the one truly useful thing an agent has done for me.

Instinct: Overall, I don't like the fact that Instinct works mainly through your text messages vs. a dedicated app. While that's very convenient in certain ways, I don't like the idea of seeing email (bad, no fun) in my texts (good, fun) — mixing the two feels wrong.

However, I have to hand it to Instinct — it found a Paperless Post invite for a party that I would otherwise have completely missed in my personal email. It was the only agent to pull that one out for me.

Dot: Dot did something truly useful that required a lot of context, and it did all on its own. It noticed an older email exchange from last month with my tax accountant (I had filed for an extension, due in October). Dot noticed my accountant never confirmed he actually filed my taxes — yikes! This actually really saved me! (Don't worry, the taxes had indeed been filed.)

Finding an older — but important — email exchange that I hadn't closed the loop on is exactly what I want from an AI agent/assistant. I feel like 90% of things I'd rather do myself, but my human brain gets easily distracted and forgetful, and there are plenty of things I forget to deal with or get distracted.

Winner: Dot. Also me, for not going to jail for tax evasion.

Challenge #2: Order me lunch.

I asked each agent to order me a salad at a specific local restaurant. Because I didn't want to annoy real humans, I did the orders for pickup, to avoid any confusion or multiple separate deliveries.

This turned out to be a real fiasco, and I learned my lesson: it would have been infinitely easier for me to just do it myself.

Muse: Initially, Muse was very helpful. I accidentally gave it the wrong restaurant name, but Muse helped me find the right place and pulled up the correct menu options for me to see.

I had already connected my credit cards with Stripe, so I figured this would be easy. It offered up my debit card or another Mastercard, which I assumed was my regular credit card (I had just gotten a new card in the mail and didn't recognize the last four digits).

When I finally went to check my wallet, I discovered it was a mistake — it was actually the card connected to my health insurance-related HSA account, which is only approved for medical expenses.

By the time I straightened this mess out, I had already moved on to placing orders with Instinct and Dot. When I went to pick up my orders at the restaurant, there were only two bags with my name on them. Sure enough, I had gotten so distracted with the other orders that I never confirmed with Muse about placing the order, and it never sent through. (Can you see now what I was saying before about how I get distracted and don't finish tasks?)

Instinct: The most annoying part about Instinct, again, in my opinion is that it's over text messages. That means there were some quirks when I tried to text on my laptop — sometimes it failed to send as SMS. But after a few fails, Instinct was able to place the order relatively quickly. Well, sort of.

All told, this took 9 separate text messages on my end — not including Instinct's responses. It is hard for me to imagine that this was at all easier than just going onto the restaurant's website or UberEats and doing it myself.

Although the process was fairly painless, there was one thing I didn't like: it put the other through with no tip (!!!) and didn't ask me if I wanted to add one.

Dot: Somehow, this was the most difficult to get to work. It kept getting tripped up by the 6-digit code sext by text needed to login, but it kept failing (I had to get the code texted 3 separate times), and the browser it created for me to enter wouldn't let me type into it. A mess, basically, but finally it worked.

Winner: None. I feel very confident in saying that it would have been infinitely easier to just place the order myself through regular means. It's possible that it would be easier to order in the future, since I've already done the work of setting it up once. But I've learned my lesson.

Challenge #3: Build me a website

I have an old personal/professional website, but it's due for a refresh. I have terrible aesthetic sense and don't want to spend much time designing a site. Seems like a good job for AI to do for me!

Muse: I appreciated that, unlike Dot and Instinct, Muse didn't use the photo of my face from my byline photo (it seems very weird to have a giant photo of your own face on a professional website).

But all three basically did the same thing: pulled the info from my author bio on Business Insider, selected some recent articles as clips, pretty basic stuff.

Instinct: The design here was the most boring, and in a way I wouldn't even know how to make it look better (terrible aesthetic sense!). Weirdly, the selected article it pulled for me were random ones from over a year ago.

Dot: The look and design were probably the best here, and it pulled a decent mix of articles I'd want to showcase. But GOOD GRIEF the tagline here is so corny that I'm sort of embarrassed to even show you, even though I didn't write it myself:

Winner: Based on the mockups it made with design alone, I'd go with Dot. I think I could work with this. But all three of these made such cringey, cheesy copy about me that it honestly made me feel genuinely depressed. Is this who I am? Yuck!

Obviously, I'd have to rewrite all the copy myself, and pick the articles for clips — and at this point, is this even saving me any time beyond being a very generic template? Ah well.

Conclusion: The biggest challenge with all of them was figuring out what kind of task an agent is well-suited for.

Most of all, I found that trying to manage three different agents at the same time was a huge hassle. I want AI agents to be like a wife — making my life easier by anticipating my needs, not a husband who simply does chores when told. But this has backfired on me: now I have three wives, and they're all nagging me and I'm forgetting which is which. Ultimately, I don't recommend AI polygamy. May my experiment with it help you choose your bride.

• Sundar Pichai said he uses AI agents to track Google's model development and internal discussions.
• The bots summarize updates and monitor how Google's computing resources are used.
• Pichai said humans still make consequential decisions about resource allocation.

Even Google's CEO needs help keeping up with Google.

On the Sources podcast released Wednesday, Sundar Pichai described to host Alex Heath how he delegates some of the information-gathering that comes with running the tech giant.

“It could easily take me an hour a day to kind of catch up, what's happened in the last 24 hours, right?" Pichai said. "But now I have agents running which summarize and bring that information to me. I can still go deeper, and I do so often."

Pichai said that his AI agents give him a way to "understand the model development arc," figure out how Google's computing resources are being used, and follow threads spread across numerous internal chat groups without having to read through every conversation himself.

“Similarly, there are agents with telemetry into our compute usage by product area, efficiency, utilization, and giving me inputs and insights, you know," Pichai added. "I think it's made all of us, you know, be better at what we do."

That doesn't mean Pichai has handed over the important calls to AI. He said humans — including himself — remain directly involved in consequential decisions about allocating computing resources.

Managing agents is becoming a skill in its own right, giving some workers a new set of headaches, from checking the bots' output to preventing them from duplicating work or straying beyond their assignments. Business Insider previously reported that the need to manage agents is making everyone a boss without higher pay.

Delegating to bots doesn't necessarily make work easier, either. A Cisco engineering director who manages more than 10 agents told Business Insider that overseeing them involves more task switching and can make work feel more intense without shortening his days.

For the Google CEO, however, continuous work is a plus.

"So because your agents, they're running in the cloud, they're running 24/7, they have your context, and so they can pick up things where you left off," Pichai said. "It's a continuum there. By the time it's doing that, you would be applying yourself to the next problem and so on."