As cybersecurity spending approaches $215B globally, enterprises face a important hole: assaults now unfold in seconds whereas detection techniques constructed for human-speed threats take weeks to put in writing new guidelines. AI-powered adversaries execute 1000’s of reconnaissance makes an attempt, adapt ways 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 harm 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 functions with enterprise context to generate detections tuned particularly to every group. By means of federated queries that retrieve knowledge on-demand somewhat 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 an alternative of disconnected alerts. Early prospects have diminished imply time to detect and reply to important safety occasions by 94%, with one know-how firm discovering multimillion-dollar cloud spend financial savings and shadow exercise invisible to current 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 Collection A spherical, and far, rather more…
Who have been your traders 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 prime VCs together with Concept Ventures, Lockstep, Two Sigma Ventures, Netz Capital, Squared Circle Ventures, Kedem Ventures, Sunflower Capital, and outstanding cybersecurity trade 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 are actually unfolding in seconds, not days, and by no means occur in the identical approach. Conventional safety stacks have 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 approach to perceive relationships throughout your technical and enterprise setting and supply steady safety to your property. It powers the complete SecOps lifecycle throughout detection, correlation, enrichment, investigation, response, and remediation – and you’ll select which actions must be carried out by an analyst or the system.
Your entire safety knowledge is now obtainable so that you can speak with and act on, remodeling the analyst’s job from knowledge meeting to decision-making. We generate full assault tales: correlated, contextualized narratives that span the complete kill chain throughout each knowledge supply. Not a group of associated alerts. A coherent rationalization 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 remaining. We will connect with a single knowledge supply and instantly generate higher detections, then broaden to switch the whole SIEM when a buyer is prepared.
The outcomes: we’re working with a few of the largest enterprises on the planet. Clients utilizing Artemis have diminished their imply time to detect and reply to vital safety occasions by 94%. We’re already in manufacturing throughout monetary providers, know-how, 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 a few of the most consequential safety platforms within the trade – 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 essentially modified in twenty years. The hole was widening quick, and patching AI onto the outdated 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 totally 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 precise group it’s defending. We study every buyer’s setting deeply – mapping how customers, machines, cloud workloads, identities, and functions 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 info already lives – current SIEMs, knowledge lakes, cloud-native shops – so detection high quality isn’t tied to how a lot knowledge you’ll be able to afford to ingest. Second, our detections are autonomous: multi-step reasoning brokers that dynamically question knowledge, cause about context, and ensure threats earlier than surfacing an alert – they usually get smarter with each incident. Third, we ship full assault tales, not remoted alerts – correlated narratives that give groups the complete image and clear subsequent steps.
Anthropic 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 every of a choose few cybersecurity firms working in deep collaboration with Anthropic, integrating Claude’s reasoning capabilities instantly into the platform to defend in opposition to precisely these sorts of threats.
What market does Artemis goal and the way large is it?
We’re going after the SIEM – the mind of safety operations – which sits on the middle of a $30+ billion market.
Greater than 60 CISOs our traders spoke with, and over 100 that we interviewed ourselves previously 12 months, listed SIEM as a prime three precedence class to leverage AI and displace incumbent know-how.
Our prospects are CISOs and safety leaders at massive enterprises – firms in extremely regulated industries like monetary providers, know-how, 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 pressured to drop knowledge to regulate prices – creating blind spots that attackers exploit. That’s the issue we resolve. We’re doing all of it in a different way.
What’s what you are promoting mannequin?
Enterprise SaaS with annual subscription contracts.
Legacy SIEMs value by knowledge quantity – which implies greater firms 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 throughout the first integration.
Our structure additionally means we are able to begin delivering worth from a single knowledge supply and broaden to switch the whole SIEM when the client is prepared.
How are you getting ready for a possible financial slowdown?
Cybersecurity is without doubt one of the final price range 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 crew 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 crew.
The businesses we promote to are additionally actively seeking to consolidate their safety stack and cut back SIEM prices – which truly makes our worth proposition stronger throughout a slowdown, not weaker.
What was the funding course of like?
The increase mirrored two issues: the pace at which we reached manufacturing outcomes, and the scale 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 have been even out of stealth, purely via phrase of mouth.
That pace 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 might have taken a robust 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 via a tectonic shift. Cisco’s acquisition of Splunk, aggressive value hikes throughout the board – CISOs are actively searching for an alternate. 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 most important challenges that you simply confronted whereas elevating capital?
Actually, we have been lucky. The mixture of deep area expertise in safety operations, early enterprise traction, and a market going via a generational shift meant we had sturdy investor curiosity from the beginning. We have been within the uncommon place of being oversubscribed and having to show down capital.
Actually, we have been lucky. The mixture of deep area expertise in safety operations, early enterprise traction, and a market going via a generational shift meant we had sturdy investor curiosity from the beginning. We have been within the uncommon place of being oversubscribed and having to show down capital.
What elements about what you are promoting led your traders to put in writing the verify?
A couple of issues. First, the crew. 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 crew at Irregular Safety and constructed large-scale ML techniques at Twitter.
We’ve independently constructed the detection engines behind two of essentially the most profitable safety merchandise of the final decade – that is the third iteration of that structure, constructed from scratch.
Second, the pace of execution. What we’ve in-built seven months since founding is forward of our authentic 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 large 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 Collection 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, traders concentrate.
What are the milestones you intend to realize within the subsequent six months?
Scale the client base aggressively – we’ve got sturdy enterprise demand and have to convert that into manufacturing deployments.
Develop the engineering and go-to-market groups to satisfy that demand.
Deepen the platform’s response capabilities; we’re transferring towards totally autonomous response guided by enterprise context.
We’re constructing towards a future the place AI defends in opposition to AI.
What recommendation are you able to provide firms in New York that shouldn’t have a recent injection of capital within the financial institution?
We have been in stealth with no web site and no public presence, and enterprise prospects discovered us via phrase of mouth alone. That solely occurs if you’re fixing an actual, pressing drawback and your product truly works.
If you will get to that time – the place the market is pulling you ahead somewhat than you pushing into it – the capital will observe. New York is an unimaginable metropolis for constructing enterprise firms 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 current 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, but it surely’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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