Two kinds of work you want AI to do in a SOC

1. Work you want off your plate. Alert triage is the obvious example: every alert deserves a real investigation, most of them turn out to be noise, and they arrive at 3am as happily as at noon. Nobody wants help with this work. They want it gone. That’s the half Intezer has spent years building. Autonomous triage that investigates every alert at forensic depth, around the clock, and only interrupts a human when something actually needs human judgment.
2. Work you want to keep, but accelerate. Deciding what to do with an escalation. Writing the incident report. Picking apart the weird binary someone found on a build server. Chasing a hunch across five systems. For this work you don’t want a replacement. You want to be a 10x version of yourself.

Today we’re shipping the second half.

We rebuilt the Intezer MCP server from the ground up, and it turns the AI platform your team already lives in, Claude, Codex, Cursor, or any MCP client, into a full security workspace: your cases, your alerts, file and URL verdicts, live SIEM and EDR telemetry, tuning rules, all of it. We had an MCP server before, and it was a fine way to ask Intezer questions from a chat window. This one is built around a bigger idea: your AI workspace should be able to do everything you can do in Intezer, then combine it with everything else you have access to.

If you read our piece on making sense of the 2026 SOC stack, this release is the missing connection between the top two layers. Detection tools are the hardware. The AI SOC is the operating system that turns raw signals into investigated verdicts and institutional memory. AI platforms like Claude are the applications where people actually work. This release plugs the operating system into the applications.

Watch one investigation, end to end

The video walks through one escalated case, but the pattern behind it is the real story. Intezer’s autonomous triage investigates every alert to forensic depth and resolves what it can on its own. What lands in front of a human is the residue. Cases where the technical facts are settled but the decision still needs judgment, usually because it turns on business context no security tool can see. Was this data share authorized? Is this vendor one we actually work with? Escalating those isn’t a triage failure, rather it’s the line where execution ends and judgment begins.

Putting Intezer inside your AI workspace is what makes that handoff productive. Pick up a case in Claude, Codex, or Cursor and you inherit the full investigation Intezer already ran, plus its recommendation, with a partner that can reach the context security tools never had: your email, Slack, the ticket queue. You keep the decision; it does the legwork around you at machine speed, pulling the case, cross-referencing your systems, documenting the verdict, writing a tuning rule. What used to be an afternoon of pivoting between consoles becomes a short, supervised exchange.

That’s the point of the combination: the autonomous half absorbs the scale, the assistive half carries the judgment, and every call you make feeds back as logic that makes the autonomous half smarter. You’re not handing off your work; you’re making judgment calls with the context, evidence, and follow-through already assembled around you.

The same question, with and without Intezer

Same alert, two ways to handle it. On the left, Claude on its own takes the impossible-travel sign-in and works it by hand. It reasons well and gets close — managed device, MFA passed, probably real travel — but it can’t collect evidence from the endpoint to confirm, so the last step falls back to a human checking the laptop. And that’s one alert; almost 4,000 more are still waiting behind it. One analyst, one alert at a time, with no way to run it across the whole team. On the right, the same alert inside the AI SOC: Intezer triages every alert around the clock, closes the ~98% that need no action, and escalates only the ~2% that genuinely need a person. Claude is where you pick those up so you can stop grinding the queue and start supervising the few cases that actually need you.

Most of the org knowledge an investigation needs is already centralized in Intezer. That’s the whole point of the platform. But some context only ever lives with you: a procurement thread in someone’s inbox, a Slack message from three weeks ago, a calendar invite. With Intezer connected on one side and your IT and communication stack on the other, your AI workspace can cross-reference both in a single investigation.

Why not plug Claude into all security tools directly?

You could also wire your AI client straight into each security tool yourself. Most of them ship an MCP these days. Two things make that a worse deal than it looks. First, the integration work is now yours: stitching a dozen connectors together, learning each product’s query quirks, and getting back a pile of disconnected results instead of one correlated picture. Second, raw tool access still isn’t investigation. With every EDR, SIEM, and intel feed wired in, the model can read your data, but it can’t collect evidence off an endpoint, run memory forensics, or weigh conflicting signals into a verdict it will actually stand behind, which is exactly where Claude stalls on the left in above image.

Intezer already did both jobs. One connector hands the model a SOC’s worth of normalized cases, verdicts backed by real forensic evidence, and cross-tool correlation. An AI platform does its best work standing on a real foundation of security knowledge, not on a dozen raw feeds it has to assemble itself.

Investigate and close the cases Intezer escalates to you

This is where analyst hours should go, so it’s where the MCP goes deepest. Whatever the alert type, the shape is the same: pull the case, build on everything the autonomous triage already found, cross-reference your other systems, decide interactively with you, and close with evidence.

And “pull the case” carries real weight here. A case from Intezer is not a bare ticket. It arrives with everything triage already did: the evidence it collected, the SIEM and EDR queries it ran, the forensic analysis of each artifact, the verdicts it reached. You’re not starting from a blank page; you’re picking up a deep investigation and taking it the last mile.

“Pick up the oldest escalated open case and let’s investigate it together.”

The clip above takes an impossible-travel alert. The MCP brings the full login history including every IP and geo, and who else touched the same address as well as your AI workspace cross-references calendar and Slack for travel context. When the evidence still isn’t conclusive, it can ask the user directly and close on their answer, so the one human check that actually mattered takes seconds instead of becoming a follow-up ticket.

Make tomorrow’s autonomous triage smarter

If a case should never have reached you, closing it is half the job. The other half is making sure it never reaches you again.

“We keep getting this exact false positive. Write a tuning rule so it never escalates again, then retriage the case.”

Claude inspects the alert’s triage indicators, drafts a narrowly scoped tuning rule, and tests the pattern against the real alert object before proposing anything. It checks whether an existing rule should be extended instead of creating a near-duplicate. It asks the question every detection engineer should ask: could an attacker hide inside this rule? Then it pushes the rule to Intezer for your approval and retriages the affected alerts so the fix applies immediately.

Tuning runs both directions, too. The same mechanism can tell the autonomous triage to always escalate a pattern it can’t yet call malicious with confidence, so the genuinely ambiguous cases land in front of a human by design, not by luck.

This is where the two halves of the AI SOC meet. Every rule your AI workspace writes makes the autonomous half smarter, which means fewer escalations next month, which means the time you spend supervising keeps shrinking. The system compounds.

From case to incident report in one prompt

When a case turns into a real incident, the hours after containment go to reconstruction: which alerts were related, which machines were touched, what happened first, and what to tell leadership.

“Write an incident report for the latest case we worked on — timeline, affected assets, and an exec summary I can send to the CISO.”

Your AI workspace pulls the case and its full activity trail from Intezer, expands across the users, devices, and IPs involved, and rebuilds the timeline from the forensic evidence already on file. Then it writes the report with an executive summary up top, technical detail below, in your template if you have one, and finally exports it to a clean, brand-styled PDF you can send as-is. The data was always in Intezer; the report was just assembly. Now assembly is one prompt.

Threat hunting: start from a lead, not an alert

Not every investigation starts in the queue. Sometimes it starts with your CISO forwarding an article about a campaign that’s hitting your industry.

“Here’s a writeup of a new campaign [link]. Check whether any of these IOCs appear anywhere in our environment, and analyze anything you find.”

Your AI workspace extracts the indicators and techniques from the writeup, sweeps your environment through Intezer’s SIEM and EDR query tools, and returns the matching assets, alerts, and artifacts for analysis. When you find something worth a closer look, you can fire deep forensics to go one step further with your hunt.

How it works

The Intezer MCP server is hosted by us. You authorize over OAuth from any MCP client: Claude (Desktop, Code, or claude.ai), ChatGPT, Codex, Cursor, or anything else that speaks the protocol.

Under the hood it exposes 66 tools covering the full case lifecycle: search and fetch cases and alerts, file and URL analysis, live queries against more than a dozen SIEM and EDR products in their native query languages (KQL, SPL, XQL, SDL, and the rest, with per-vendor syntax guides built in so the model gets them right), tuning rules and AI instructions, retriage, and case editing.

This architecture is what makes the two halves described above work as one system: the autonomous half clears work off your plate, while the assistive half accelerates the tasks where you still want to stay in the loop.

Getting started

1. If you’re already an Intezer customer, an Intezer admin creates an MCP OAuth application under Account Settings → MCP OAuth Applications.
2. Add Intezer as a custom connector in your AI client such as Claude, ChatGPT, or any MCP client. Point it at the hosted server, and authorize with your own Intezer login over OAuth.
3. Open with one prompt: ask it to pick up your oldest open escalation.

The autonomous half investigates everything, around the clock, so your team only sees what matters. The assistive half makes the time you spend on what matters dramatically shorter. One system of record and detection logic underneath both: your cases, your verdicts, your tuning rules, your institutional memory, working for you whether the investigation runs inside Intezer or inside your AI workspace.

AI executes. Humans supervise. And now the supervising got a lot faster too.

If you’re not an Intezer customer yet, book a demo and we’ll show you both halves at once: autonomous triage working every alert around the clock, and a co-pilot that helps your analysts close the escalations that do reach them 10x faster.

The post The other half of the AI SOC: Intezer, now inside your AI workspace appeared first on Intezer.

Modern SOC teams face some real challenges. They are drowning in alert volume, short on experienced analysts, and facing a new generation of AI-driven attacks that operate faster than humans can respond. This combination is eroding SOC effectiveness, slowing response times, and creating blind spots where real threats hide in low-severity alerts that teams no longer have the time or capacity to investigate.

To meet this moment, Intezer is proud to unveil Intezer Forensic AI SOC, the only AI SOC platform battle-tested inside some of the world’s most targeted and security-mature organizations. Already trusted by more than 150 enterprises, including 15 of the Fortune 500, the platform brings forensic-grade accuracy, full alert coverage, and sub-minute triage to modern security operations.

Why enterprises need a Forensic AI SOC

As attack surfaces grow, many organizations turn to MDR providers for 24/7 alert triage. But MDRs often operate as black boxes with inconsistent quality, high escalation rates, and limited visibility, leaving low-severity alerts unaddressed and creating gaps adversaries can exploit.

Most “AI SOC” tools depend entirely on AI agents for alert triage and investigation. This leads to surface-level results, slower performance, and higher compute usage, limiting their ability to process large alert volumes, especially low-severity signals where threats frequently hide.

The way forward requires an approach that removes SOC bottlenecks while delivering stronger, more reliable security outcomes. 

Why this matters now

The recent Anthropic AI espionage report marks a turning point. Threat actors are now weaponizing AI agents to automate full intrusion chains at machine speed.

These attacks often leave behind subtle, low-severity breadcrumbs that traditional SOCs and MDRs overlook. Without full alert coverage and forensic-grade triage, organizations cannot detect or contain AI-driven campaigns before they escalate.

This is precisely the gap Intezer’s Forensic AI SOC was built to close.

Watch session on how security leaders prepare for the new era of AI-orchestrated cyber attacks.

The Forensic AI SOC advantage

Intezer Forensic AI SOC flips the AI SOC model on its head. Instead of solely relying on AI Agents and LLMs, our platform combines AI agents and automated orchestration of  deterministic forensic tools, to mimic the triage and investigation methods used by elite responders and perform deep, accurate investigations at speed and scale.

Every alert is examined through a forensic lens using Intezer’s battle-tested capabilities, including endpoint forensics, reverse engineering, network artifact analysis, sandboxing, and other proprietary methods. These are paired with the adaptive research and reasoning of multiple LLMs to ensure both depth and flexibility in every investigation.

Intezer Forensic AI delivers:

• 100% alert coverage, including low-severity alerts often ignored by SOCs and MDRs
• Fewer than 4% of alerts escalated for human review
• 98% accurate, consistent verdicts backed by deterministic evidence
• 1-minute median triage time
• Predictable, scalable pricing tied to endpoints, not alert volume or costly model usage
  

Enterprises get both the intelligence of AI and the rigor of forensics, without sacrificing speed, cost, or accuracy.

Proven in the world’s most targeted enterprises

Intezer supports over 150 enterprises, including 15 of the Fortune 500, across verticals such as finance, tech, pharma, critical infrastructure, hospitality and more. These organizations operate some of the most complex and heavily targeted environments in the world and rely on Intezer to keep their businesses secure. 

“Intezer’s AI-driven triage has been transformative for our SOC. It integrates seamlessly with our existing systems and delivers analyst-level investigations at scale, giving our team the confidence that every alert is handled with forensic accuracy.”

Branden Newman, CTO, MGM Resorts International

Built for the growing demands of enterprise SOCs

Enterprise SOCs must respond not only to rising alert volume, but also to increasing business pressure for speed, consistency, and measurable risk reduction. Companies using Intezer Forensic AI SOC enjoy:

• Lower business risk
  Every alert, including low-severity signals used by modern attackers, is investigated with dramatically shortened MTTR.
• Predictable, cost-efficient pricing
  Pricing aligned to endpoints avoids the unpredictable costs of LLM-heavy AI SOCs.
• Instant time to value
  Hundreds of integrations enable rapid deployment and immediate time-to-value without training models on customer data.
• Doing more with less
  Reduce MDR dependence and automate analyst workloads to optimize budgets and expand SOC output.

Built by security experts, for security experts

Intezer was founded and shaped by world-class SecOps leaders, security researchers and incident responders who have spent their careers defending some of the most targeted organizations and building foundational cybersecurity technologies.

Our leadership team includes pioneers who helped create and scale major cybersecurity companies. This firsthand experience responding to advanced threats, operating high-pressure SOC environments, and building products used by thousands of security teams worldwide directly informs how Intezer designs its technology.

We understand what analysts need, speed, accuracy, transparency, and trustworthy automation, because we’ve lived those challenges ourselves.

Intezer Forensic AI SOC reflects that operational DNA with a platform built not by generic AI engineers, but by practitioners who have spent years reverse engineering malware, hunting nation-state adversaries, leading global IR engagements, and building tools that analysts rely on every day.

Join the future of the SOC, today!

The SOC is entering a new era. Machine-scaled attacks demand an approach grounded in both forensic rigor and adaptive AI enabling consistent, accurate investigations to defend the enterprise. 

To explore how Intezer’s Forensic AI SOC can strengthen your operations, schedule a conversation with a product expert today!

The post Introducing Intezer Forensic AI SOC appeared first on Intezer.

There’s been an explosion of buzz around the AI SOC market. More than 40 vendors are now claiming to do something in this space, but as with many emerging technology categories, the result is a lot of excitement and a lot of confusion.

In this video and in the article below it, I want to provide some clarity. What exactly is “AI SOC”? Where did this category come from? And how can security teams cut through the noise to find real value?

The origins of the AI SOC: An old problem meets new tech

The rise of the AI SOC stems from two converging forces. A very old problem and a very new technology.

The old problem is the persistent talent shortage in cybersecurity combined with the overwhelming volume of security alerts. Security teams have been drowning in these alerts for years, struggling to keep up with investigation and response.

The new technology is AI, especially large language models (LLMs) and adjacent innovations, which open up an opportunity to finally address that shortage by automating some of the human decision-making process.

The 3 layers of security operations

To understand where AI fits in and how it can help, let’s zoom out and look at the broader security operations stack. 

There are three main layers:

Detection (SIEM, XDR) is the first level which handles converting raw logs and other telemetry data into actionable alerts.

Triage and investigation (SOC) is the middle layer where human analysts determine which alerts are real incidents worth escalating.

Response and case management (SOAR) is the final layer that manages incident remediation with case assignment, and workflow automation.

Each layer presents opportunities for AI. For example, in SIEM/XDR, AI can improve detection logic and reduce false positives. For SOC, AI can simulate the investigative reasoning of human analysts. And when applied to SOAR, AI can accelerate workflow creation and automate routine case handling.

In each of these areas, vendors are loosely using the term AI SOC to describe what they are doing. And that is why it’s important to know what problem you are trying to solve and which ‘AI SOC” solution is appropriate for you.

Read about how AI is redefining detection engineering.

What AI SOC usually means

All that said, when people refer to AI SOC, they’re usually talking about that middle layer. The part focused on automated alert triage, investigation, and escalation.

That’s where Intezer focuses: providing 24/7 managed alert triage, investigation, and response powered by a decade of deep forensic analysis tooling combined with flexible and adaptable LLMs.

Our system automatically investigates alerts, surfaces only what truly requires attention, and escalates only up to 4% of alerts to human analysts.

This is where the market’s energy, and customer need, are currently concentrated. Teams want to scale their response capabilities without adding headcount, and AI SOCs make that possible.

How to evaluate AI SOC vendors

With so many vendors entering the field, it’s important to evaluate them based on clear, measurable criteria. Some of the key metrics that I’m hearing from our customers and prospect that they consider, include:

• Accuracy: How precise are the AI-driven investigations?
• Speed: How quickly can alerts be triaged?
• Scale and coverage: Can the system handle all your alerts in a timely fashion?
• Noise reduction: What percentage of alerts still require human review?
• Context and transparency: Can you understand how the AI reached its conclusions, or is it a black box?

For more on this, see our guide to evaluate AI SOC tools (with questions to ask vendors).

The road ahead

AI SOC is one of the most exciting and fast-evolving categories in cybersecurity. It’s also one of the messiest, but that’s often a sign of real innovation happening.

For years, the industry has been searching for a way to truly solve the alert overload and talent shortage problem. With the arrival of AI-driven investigation technology, we’re finally seeing that vision come to life.

A recent SACR market analysis report examined these metrics across leading AI SOC vendors which can be very helpful for evaluating which solution is right for you. And I definitely recommend reading about Intezer in the report 🙂. 

At Intezer, we’re proud to help security teams reduce noise, focus on real threats, and scale their operations intelligently.

If you’re exploring this space, we’d love to be your partner in building a smarter SOC.

The post Making sense of the AI SOC market appeared first on Intezer.