As cybersecurity spending approaches $215B globally, enterprises face a vital hole: assaults now unfold in seconds whereas detection techniques constructed for human-speed threats take weeks to jot down new guidelines. AI-powered adversaries execute 1000’s of reconnaissance makes an attempt, adapt techniques in actual time, and by no means repeat the identical assault sample twice, leaving safety groups manually stitching collectively context throughout dozens of fragmented instruments lengthy after injury happens. Artemis addresses this disparity with an AI-native safety platform that builds a dynamic knowledge mannequin from every buyer’s personal telemetry, fusing behavioral logs throughout customers, machines, cloud workloads, and purposes with enterprise context to generate detections tuned particularly to every group. By means of federated queries that retrieve knowledge on-demand quite than requiring upfront ingestion, Artemis processes billions of occasions per hour at a fifth of conventional SIEM prices whereas autonomously investigating each sign and surfacing coherent assault tales as a substitute of disconnected alerts. Early prospects have decreased imply time to detect and reply to vital safety occasions by 94%, with one expertise firm discovering multimillion-dollar cloud spend financial savings and shadow exercise invisible to present instruments in the course of the first scan.
AlleyWatch sat down with Artemis Cofounder and CEO Shachar Hirshberg to study extra in regards to the enterprise, its future plans, emergence from stealth, latest funding announcement, which features a Seed and Sequence A spherical, and far, rather more…
Who had been your buyers and the way a lot did you increase?
We raised $70M in funding, led by Felicis with First Spherical Capital and Brightmind Companions doubling down, alongside high VCs together with Principle Ventures, Lockstep, Two Sigma Ventures, Netz Capital, Squared Circle Ventures, Kedem Ventures, Sunflower Capital, and distinguished cybersecurity business leaders, together with founders of Irregular AI and Demisto, the previous CEO and CTO of Splunk, and senior executives from CrowdStrike, Palo Alto Networks, Microsoft, and Okta.
Inform us in regards to the services or products that Artemis provides.
Assaults at the moment are unfolding in seconds, not days, and by no means occur in the identical manner. Conventional safety stacks had been constructed for a world of static guidelines, fragmented instruments, and guide investigation. That world doesn’t scale to the brand new actuality.
Artemis is an AI-native safety platform in-built an AI-native technique to perceive relationships throughout your technical and enterprise setting and supply steady safety to your property. It powers the total SecOps lifecycle throughout detection, correlation, enrichment, investigation, response, and remediation – and you’ll select which actions ought to be carried out by an analyst or the system.
Your whole safety knowledge is now out there so that you can discuss with and act on, reworking the analyst’s job from knowledge meeting to decision-making. We generate full assault tales: correlated, contextualized narratives that span the total kill chain throughout each knowledge supply. Not a group of associated alerts. A coherent clarification of what’s taking place and why it issues.
As an alternative of studying a proprietary question language to analyze an incident, analysts describe what they’re searching for in plain language and let the system deal with the remainder. We are able to hook up with a single knowledge supply and instantly generate higher detections, then develop to switch your entire SIEM when a buyer is prepared.
The outcomes: we’re working with among the largest enterprises on this planet. Prospects utilizing Artemis have decreased their imply time to detect and reply to vital safety occasions by 94%. We’re already in manufacturing throughout monetary providers, expertise, insurance coverage, and extra, analyzing over 15,000TB every day and billions of occasions hourly.
What impressed the beginning of Artemis?
Dan and I spent the higher a part of a decade constructing detection and AI techniques inside among the most consequential safety platforms within the business – I used to be an early engineer at Demisto and later led Amazon GuardDuty at AWS; Dan led AI/ML at Irregular Safety and constructed large-scale ML techniques at Twitter. From these seats, we each watched the identical factor occur: attackers began leveraging AI to turbocharge their operations, executing in seconds what used to take days, adapting in actual time, by no means repeating the identical playbook twice. In the meantime, the instruments defenders depend on – static guidelines, guide investigation, fragmented dashboards – haven’t basically modified in twenty years. The hole was widening quick, and patching AI onto the previous structure wasn’t going to shut it. We began Artemis as a result of we believed defenders wanted a platform constructed from scratch for this period – one which fights AI with AI.
How is Artemis completely different?
Most safety merchandise give each group the identical protection – the identical sensors, the identical guidelines, the identical alerts – no matter whether or not you’re a 50,000-person financial institution or a 2,000-person software program firm. Consider it like a house alarm system: conventional distributors set up the identical setup in a villa with a yard as they do in a tenth-floor residence. They don’t know the place your home windows are weak, which door will get used, who’s in the home, or what regular appears like for your loved ones.
Artemis builds protection that’s tailor-made to the particular group it’s defending. We study every buyer’s setting deeply – mapping how customers, machines, cloud workloads, identities, and purposes work together with one another and with the enterprise context round them – and generate detections tuned particularly to that group. Not generic guidelines. That’s one thing nobody else is constructing.
On the structure aspect, three structural variations set us aside. First, we federate queries throughout wherever the information already lives – present SIEMs, knowledge lakes, cloud-native shops – so detection high quality isn’t tied to how a lot knowledge you possibly can afford to ingest. Second, our detections are autonomous: multi-step reasoning brokers that dynamically question knowledge, purpose about context, and make sure threats earlier than surfacing an alert – and so they get smarter with each incident. Third, we ship full assault tales, not remoted alerts – correlated narratives that give groups the total image and clear subsequent steps.
Anthropic just lately documented the primary AI-orchestrated cyber-espionage marketing campaign, the place autonomous brokers executed a lot of the intrusion lifecycle. We’re one in all a choose few cybersecurity corporations working in deep collaboration with Anthropic, integrating Claude’s reasoning capabilities straight into the platform to defend towards precisely these sorts of threats.
What market does Artemis goal and the way massive is it?
We’re going after the SIEM – the mind of safety operations – which sits on the heart of a $30+ billion market.
Greater than 60 CISOs our buyers spoke with, and over 100 that we interviewed ourselves up to now 12 months, listed SIEM as a high three precedence class to leverage AI and displace incumbent expertise.
Our prospects are CISOs and safety leaders at massive enterprises – corporations in extremely regulated industries like monetary providers, expertise, and healthcare.
These organizations are spending thousands and thousands a 12 months on legacy merchandise, getting 1000’s of every day alerts in return, and watching their safety groups spend extra time sustaining damaged tooling than investigating precise threats. Information volumes develop 30-40% yearly, distributors cost by the gigabyte, and groups are compelled to drop knowledge to manage prices – creating blind spots that attackers exploit. That’s the issue we resolve. We’re doing all of it in another way.
What’s your corporation mannequin?
Enterprise SaaS with annual subscription contracts.
Legacy SIEMs worth by knowledge quantity – which suggests greater corporations pay thousands and thousands a 12 months and are penalized for wanting higher visibility.
We broke that mannequin. Artemis costs on worth delivered, not gigabytes ingested.
At one buyer, we uncovered multi-million greenback financial savings in cloud spend inside the first integration.
Our structure additionally means we will begin delivering worth from a single knowledge supply and develop to switch your entire SIEM when the shopper is prepared.
How are you making ready for a possible financial slowdown?
Cybersecurity is likely one of the final finances traces to get minimize in a downturn, and AI-driven assaults don’t decelerate when the economic system does. That mentioned, we’re constructing Artemis with capital effectivity as a core precept.
Our AI-native structure means a small, distinctive engineering workforce can ship what would historically require 200+ engineers. We went from founding to manufacturing deployment with over dozens of enterprise prospects in roughly six months with a lean workforce.
The businesses we promote to are additionally actively trying to consolidate their safety stack and scale back SIEM prices – which really makes our worth proposition stronger throughout a slowdown, not weaker.
What was the funding course of like?
The increase mirrored two issues: the velocity at which we reached manufacturing outcomes, and the dimensions of the chance.
In lower than six months from founding, we onboarded greater than ten of the world’s largest enterprises into full manufacturing. Not POCs, not pilots — manufacturing. Firms which have labored with conventional distributors for years telling us, “what you probably did in two weeks takes us a 12 months with our present supplier.” The demand got here organically – prospects reached out earlier than we had been even out of stealth, purely by phrase of mouth.
That velocity comes from being AI-native not simply within the product, however in how we construct software program. 99% of our code is written with AI. Each engineer ships 4-5 options per week – work that will have taken a powerful engineer two to 3 months only a 12 months in the past. A brand new integration in Artemis takes a day or two, versus three to 6 months at opponents. With 30 individuals, we’re producing the output of a 200-person firm.
The SIEM class goes by a tectonic shift. Cisco’s acquisition of Splunk, aggressive worth hikes throughout the board – CISOs are actively searching for another. The funding will go towards scaling our engineering and analysis groups, increasing the platform, and constructing out our go-to-market operation.
What are the largest challenges that you just confronted whereas elevating capital?
Truthfully, we had been lucky. The mix of deep area expertise in safety operations, early enterprise traction, and a market going by a generational shift meant we had sturdy investor curiosity from the beginning. We had been within the uncommon place of being oversubscribed and having to show down capital.
Truthfully, we had been lucky. The mix of deep area expertise in safety operations, early enterprise traction, and a market going by a generational shift meant we had sturdy investor curiosity from the beginning. We had been within the uncommon place of being oversubscribed and having to show down capital.
What components about your corporation led your buyers to jot down the verify?
A number of issues. First, the workforce. I used to be an early engineer at Demisto, the corporate that outlined the SOAR class and was acquired by Palo Alto Networks, and I later led product for Amazon GuardDuty, scaling it to over 80,000 prospects. Dan led the 60-person AI/ML workforce at Irregular Safety and constructed large-scale ML techniques at Twitter.
We’ve independently constructed the detection engines behind two of probably the most profitable safety merchandise of the final decade – that is the third iteration of that structure, constructed from scratch.
Second, the velocity of execution. What we’ve in-built seven months since founding is forward of our unique product roadmap by eight months. Practically 100% of our code is AI-generated. The platform processes billions of occasions per hour, and we’ve already closed massive enterprise logos.
Third, the market pull. First Spherical, BrightMind, and Lockstep invested when it was simply the 2 of us and a really early concept. By the point we had Sequence A, we had greater than dozens of manufacturing enterprise prospects with no web site, no advertising, and no outbound. When prospects discover you thru phrase of mouth alone at that stage, buyers concentrate.
What are the milestones you intend to realize within the subsequent six months?
Scale the shopper base aggressively – now we have sturdy enterprise demand and have to convert that into manufacturing deployments.
Develop the engineering and go-to-market groups to fulfill that demand.
Deepen the platform’s response capabilities; we’re shifting towards totally autonomous response guided by enterprise context.
We’re constructing towards a future the place AI defends towards AI.
What recommendation are you able to supply corporations in New York that wouldn’t have a recent injection of capital within the financial institution?
We had been in stealth with no web site and no public presence, and enterprise prospects discovered us by phrase of mouth alone. That solely occurs whenever you’re fixing an actual, pressing downside and your product really works.
If you may get to that time – the place the market is pulling you ahead quite than you pushing into it – the capital will comply with. New York is an unbelievable metropolis for constructing enterprise corporations as a result of your prospects are proper right here.
Use that proximity. Discuss to patrons early and sometimes. Don’t construct in isolation.
The place do you see the corporate going now over the close to time period?
The launch is behind us, and enterprise demand is accelerating.
Close to-term, we’re changing pipeline into income, increasing inside our present buyer base, and constructing the go-to-market engine.
We’re additionally advancing towards autonomous response – the subsequent main functionality shift. The SIEM class has been the mind of safety operations for twenty years, however it’s been working extra like an overpriced submitting cupboard. We’re constructing the substitute. The shift from static, rule-based safety to AI-native protection is inevitable. We intend to outline what that appears like.
What’s your favourite spring vacation spot in and across the metropolis?
Central Park – nothing beats a enjoyable Saturday at Sheep’s Meadow, spending time with mates.
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