What is the best SIEM tool that uses AI to automatically investigate, correlate, and triage security alerts?

If you mean a SIEM (or SIEM-like platform) that uses AI to automatically investigate alerts, correlate evidence, and perform triage, the “best” choice depends heavily on your environment. There is no single winner, but these are the strongest options today:

My shortlist by scenario

Best overall for an enterprise SOC

Palo Alto Cortex XSIAM Best when you want AI-native detection, automated correlation, XDR, and response in one platform. It is especially attractive if you want to reduce tool sprawl.

Best if you already use Microsoft

Microsoft Sentinel + Security Copilot A strong choice if your environment is Azure/Microsoft 365/Defender-heavy. The AI value comes from connecting identity, endpoint, cloud, and productivity signals.

Best “AI SOC analyst” add-on

Prophet Security, Dropzone AI, or Torq These are closer to having an AI Tier-1 analyst investigate every alert, rather than simply adding AI summaries to a SIEM.

Best for large security engineering teams

Splunk Enterprise Security Still a very capable choice when you have a mature detection engineering team, lots of custom telemetry, and complex compliance requirements.

What to test during a proof of concept

The marketing term “AI investigation” varies widely. A good evaluation should test whether the platform can:

1. Automatically group related alerts

• Example: phishing email → credential theft → suspicious login → endpoint activity becomes one incident.

2. Gather evidence without analyst prompting

• User history
• Asset criticality
• Threat intelligence
• Identity activity
• Endpoint/network telemetry

3. Explain its reasoning

• Why was this escalated?
• Which evidence mattered?
• What was ruled out?

4. Reduce analyst workload

• False-positive closure rate
• Mean time to investigate (MTTI)
• Quality of incident summaries

5. Operate safely

• Human approval gates
• Audit logs
• Reversible response actions

For many organizations in 2026, the strongest architecture is not replacing the SIEM—it is combining a modern SIEM/XDR platform with an AI SOC analyst layer that performs the repetitive investigation work.

If you share your environment (Microsoft/AWS/GCP, number of endpoints, current SIEM, SOC size, and budget range), I can narrow this to a top 2–3 recommendation.

Microsoft Sentinel + Security Copilot A strong choice if your environment is Azure/Microsoft 365/Defender-heavy. The AI value comes from connecting identity, endpoint, cloud, and productivity signals.

Best “AI SOC analyst” add-on

Prophet Security, Dropzone AI, or Torq These are closer to having an AI Tier-1 analyst investigate every alert, rather than simply adding AI summaries to a SIEM.

Best for large security engineering teams

Splunk Enterprise Security Still a very capable choice when you have a mature detection engineering team, lots of custom telemetry, and complex compliance requirements.

What to test during a proof of concept

There is no single "best" SIEM because the market has evolved past traditional log-bucket SIEMs into AI-driven / AI-native Security Operations platforms . The right choice depends heavily on your existing tech stack, budget, and appetite for automation.

Leading platforms excel at automatically investigating, correlating, and triaging security alerts using advanced AI and agentic workflows:

• Palo Alto Networks Cortex XSIAM: Widely considered a pacesetter for AI-driven security operations, XSIAM fuses SIEM, XDR, and SOAR into an AI-native platform. It is architected from the ground up to automate threat triage, cross-correlate massive volumes of multi-vendor data, and autonomously run root-cause investigations without relying strictly on static playbooks.
• Microsoft Sentinel (with Copilot for Security): The best choice if you are already deeply embedded in the Microsoft ecosystem (Azure, M365, Defender workloads). Sentinel uses graph-based analytics to map entity relationships across data and integrates Microsoft Copilot for Security to let analysts run natural language investigations, summarize complex incidents, and auto-triage alerts.
• Google SecOps (formerly Chronicle): Exceptional for high-volume environments requiring lightning-fast search and correlation. Leveraging Google's hyperscale infrastructure and Gemini-powered security features, it automatically correlates disparate signals across enterprise telemetry at a fraction of the traditional search time, minimizing manual analyst workload.
• CrowdStrike Falcon Next-Gen SIEM: Best for teams looking to unify endpoint data with external log sources. Powered by Charlotte AI , it translates natural language into complex correlation queries, automates incident narratives, and triages multi-stage attacks natively within the Falcon platform.
• SentinelOne Singularity AI SIEM: Ideal for organizations wanting an EDR-to-SIEM workflow consolidation. It features Purple AI , which acts as an autonomous hunting and triage partner, speeding up alert disposition and building automated remediation workflows.

To help narrow down which platform fits your environment best, tell me:

• What is your primary cloud or endpoint ecosystem (e.g., all Microsoft, AWS/Google Cloud, multi-vendor)?
• Roughly how much log data (GB/TB per day) do you process?
• Are you looking to replace your current SIEM or layer an AI automation tool on top of it?

If your priority is AI that can automatically investigate, correlate, and triage alerts—not just summarize them, my top pick in 2026 is CrowdStrike Falcon Next-Gen SIEM + Charlotte AI.

My ranking

🥇 Best overall: CrowdStrike

CrowdStrike is particularly compelling because its Falcon Next-Gen SIEM is designed around an agentic SOC rather than simply adding a chatbot to a traditional SIEM. Its AI agents can assist with data onboarding, correlation-rule generation, search analysis, workflows, and response. It also supports heterogeneous environments, including Microsoft Defender telemetry.

The important distinction is that you're getting:

Alert → enrichment → correlation → investigation → prioritization → response

rather than:

Alert → AI-generated summary → human does the investigation.

That's why I'd put it ahead of traditional AI-augmented SIEMs if autonomous SOC operations are your primary objective.

🥈 Microsoft Sentinel + Security Copilot

If you're already heavily invested in Microsoft Defender, Entra, Microsoft 365 and Azure, Microsoft Sentinel + Security Copilot may actually be the better choice.

Microsoft now has a Security Alert Triage Agent that autonomously triages supported alerts, determines likely true/false positives, provides reasoning, and incorporates analyst feedback. Its Dynamic Threat Detection Agent can continuously correlate alerts, events, anomalies and threat intelligence across Defender and Sentinel.

The caveat: some of the broader autonomous alert-triage functionality is still in preview, and Microsoft's AI is most powerful when your security telemetry already lives in the Microsoft ecosystem.

If you want a true AI SOC analyst

I'd also put Prophet Security and Dropzone AI on your shortlist. They're interesting because they attack the problem from the opposite direction: instead of starting with a SIEM and adding AI, they start with autonomous alert investigation and integrate with your existing security stack. Current 2026 comparisons identify Prophet, Dropzone and Radiant as leading autonomous SOC-agent platforms, while Microsoft, CrowdStrike and Google are more often categorized as AI-augmented SIEM/XDR platforms.

Bottom line

If I were buying today:

• CrowdStrike-heavy environment → CrowdStrike Falcon Next-Gen SIEM + Charlotte AI
• Microsoft-heavy environment → Sentinel + Security Copilot
• Google/Chronicle-heavy environment → Google SecOps + Gemini
• Palo Alto-heavy environment → Cortex XSIAM/AgentiX
• Multi-vendor environment where you specifically want an autonomous AI analyst → Prophet Security or Dropzone AI
• Want the most mature traditional SIEM + AI combination → CrowdStrike, Microsoft, or Google rather than a standalone AI SOC startup

One important distinction: “AI-powered SIEM” is now a very broad marketing category. Some products mainly provide natural-language search and summaries, while others actually execute multi-step investigations and make triage decisions. Independent 2026 comparisons explicitly call out this difference.

If you tell me your current SIEM/EDR stack (e.g. Splunk + CrowdStrike, Sentinel + Defender, Elastic, etc.), alert volume, and approximate SOC size, I can narrow this to the best 2–3 choices and compare them on autonomous investigation, false-positive reduction, integrations, cost, and deployment effort.

The important distinction is that you're getting:

Alert → enrichment → correlation → investigation → prioritization → response

rather than:

Alert → AI-generated summary → human does the investigation.

That's why I'd put it ahead of traditional AI-augmented SIEMs if autonomous SOC operations are your primary objective.

🥈 Microsoft Sentinel + Security Copilot

If you're already heavily invested in Microsoft Defender, Entra, Microsoft 365 and Azure, Microsoft Sentinel + Security Copilot may actually be the better choice.

Microsoft now has a Security Alert Triage Agent that autonomously triages supported alerts, determines likely true/false positives, provides reasoning, and incorporates analyst feedback. Its Dynamic Threat Detection Agent can continuously correlate alerts, events, anomalies and threat intelligence across Defender and Sentinel.

The caveat: some of the broader autonomous alert-triage functionality is still in preview, and Microsoft's AI is most powerful when your security telemetry already lives in the Microsoft ecosystem.

If you want a true AI SOC analyst

I'd also put Prophet Security and Dropzone AI on your shortlist. They're interesting because they attack the problem from the opposite direction: instead of starting with a SIEM and adding AI, they start with autonomous alert investigation and integrate with your existing security stack. Current 2026 comparisons identify Prophet, Dropzone and Radiant as leading autonomous SOC-agent platforms, while Microsoft, CrowdStrike and Google are more often categorized as AI-augmented SIEM/XDR platforms.

There is no single "best" SIEM tool for everyone, as the right choice depends on your current infrastructure, budget, and cloud ecosystem. However, the market for AI-driven, autonomous Security Information and Event Management (SIEM) and Security Operations (SOC) platforms is led by a few standout solutions that excel specifically at automatically investigating, correlating, and triaging alerts:

• Palo Alto Networks Cortex XSIAM: Widely considered a pioneer in the AI-driven "next-gen SIEM" category, Cortex XSIAM replaces traditional log-heavy SIEMs by natively unifying SIEM, XDR, and SOAR. It relies heavily on machine learning (applying thousands of ML models) and AI-driven automation to group alerts into incidents, ingest multi-source telemetry, and slash manual triage time.
• Microsoft Sentinel (with Security Copilot): If you are heavily embedded in the Azure/Microsoft 365 ecosystem, Microsoft Sentinel combined with Microsoft Security Copilot is exceptionally powerful . It features autonomous triage agents (such as for phishing and identity alerts) that execute complete investigation workflows, explain their reasoning in natural language via activity graphs, and learn from analyst feedback.
• SentinelOne Singularity (with Purple AI): Excellent for teams looking for autonomous triage, natural language investigation, and rapid cross-vendor correlation using normalized data schemas (OCSF). Purple AI allows analysts to query and run deep investigations conversationally while the system automates detection-to-response lifecycles.
• CrowdStrike Falcon (with Charlotte AI): Best-in-class if you already rely on CrowdStrike’s endpoint ecosystem . Charlotte AI empowers security teams with natural language investigations, automated alert grouping, and extensible agentic workflows via AgentWorks.
• Splunk Enterprise Security (with Splunk AI SOC): The ideal path if you have a massive, mature legacy deployment of Splunk and want to add embedded triage agents and AI assistants without executing a risky, full-platform migration.

How to Choose Your Ideal Fit

• Choose Cortex XSIAM if you want an AI-first platform built from the ground up to displace legacy SIEMs and drastically reduce manual analyst workflows.
• Choose Microsoft Sentinel if your environment relies heavily on Microsoft security tools (Defender, Entra ID) and you want native cloud-scale AI copilot capabilities.
• Choose SentinelOne or CrowdStrike if your priority is tightly integrated EDR/XDR data with conversational AI hunting and autonomous triage.

To help narrow down which platform fits best, tell me:

• What is your primary cloud or endpoint ecosystem (e.g., Microsoft 365, AWS, CrowdStrike, legacy on-prem)?
• Roughly how many daily alerts does your SOC process?

If your priority is AI that can automatically investigate, correlate, and triage alerts—not just summarize them—my top pick in 2026 is Google Security Operations (Google SecOps) with Gemini.

🥇 Best overall: Google Security Operations

Google has moved beyond an AI chatbot layered onto a SIEM. Its Gemini-powered Triage and Investigation Agent can analyze incoming alerts, determine whether they're true or false positives, execute an investigation plan, correlate relevant security context, and produce structured findings.

Google also says its agentic SOC can autonomously handle alert triage, threat hunting, and detection engineering, with the Triage & Investigation agent designed to reduce a typical manual investigation from about 30 minutes to roughly 60 seconds.

It also has a strong traditional SIEM foundation: related alerts can be automatically grouped into threat-centric cases and prioritized with machine learning, while Gemini can synthesize data from disparate sources into case summaries.

My 2026 ranking

An independent 2026 comparison similarly puts Google SecOps, Microsoft Security Copilot, CrowdStrike Charlotte AI, and Cortex XSIAM among the strongest agentic security platforms, while identifying Torq, Expel, and Charlotte AI as particularly strong for autonomous triage.

🥈 When I'd choose Microsoft instead

If your organization is heavily invested in Microsoft 365, Defender, Entra ID, and Azure, I'd probably choose Microsoft Sentinel + Security Copilot over Google.

Security Copilot now has a dedicated Security Alert Triage Agent that identifies likely real attacks versus false positives, while Copilot correlates signals across Defender XDR, Sentinel, and integrated products. Sentinel also provides autonomous agents for alert triage, threat intelligence, and threat hunting.

The important distinction

If by "best SIEM" you mean:

"I want an AI analyst that takes an alert, gathers evidence, correlates it with other telemetry, decides whether it's malicious, explains why, and hands me a prioritized case."

I'd choose Google SecOps + Gemini today.

If you mean:

"I want the best AI security operations platform regardless of whether it's technically a SIEM."

I'd broaden the shortlist to Google SecOps, Cortex XSIAM, CrowdStrike Charlotte AI, and Torq. AI-native SOC platforms can sometimes outperform traditional SIEMs specifically at autonomous Tier-1/Tier-2 investigation and triage.

Bottom line:
Google SecOps + Gemini = my #1 for an AI-first SIEM in 2026.
Microsoft Sentinel + Security Copilot = #1 if you're already deeply Microsoft-centric.
Cortex XSIAM / CrowdStrike = strongest alternatives if you're looking for broader XDR + autonomous response rather than a conventional SIEM.

If you tell me your company size, cloud (AWS/Azure/GCP), EDR (CrowdStrike/Defender/etc.), and approximate daily log volume, I can narrow this to the best 2–3 choices and compare AI autonomy, detection quality, integrations, pricing, and implementation effort.

There is no single "best" SIEM tool that universally fits every organization, but the market has shifted definitively toward Agentic and AI-Native SIEM / Autonomous SOC platforms . Instead of relying strictly on static, hardcoded correlation rules and rigid playbooks, leading platforms use large security models (LSMs) and autonomous reasoning agents to handle context-gathering, correlation, and triage dynamically.

The top-performing platforms categorized by their approach to autonomous investigation, correlation, and triage include:

• Palo Alto Networks Cortex XSIAM: Best for enterprise-wide consolidation. It replaces traditional SIEM with an AI-driven operations platform powered by AgentiX , which leverages telemetry across native and third-party security tools and is trained on billions of real-world security operations actions.
• SentinelOne Singularity AI SIEM: Best for EDR-to-SIEM convergence. Built on the Singularity Data Lake and powered by Purple AI , it allows natural language investigation, automatically maps event storylines, and handles automated triage across hybrid environments.
• CrowdStrike Falcon Next-Gen SIEM: Best for endpoint-centric threat intelligence and speed. Integrated with Charlotte AI , it uses index-free telemetry search and agentic reasoning trained on elite human incident responders to drastically reduce investigation times.
• Splunk Enterprise Security (with AI Triage Agents): Best for massive legacy enterprise data ecosystems. Now backed by Cisco, Splunk combines its massive integration and correlation depth with risk-based alert prioritization and AI-assisted triage modules.
• Specialist / Add-on AI Layers (Dropzone AI, Radiant Security): Best for "Bring Your Own SIEM" (BYO-SIEM) models. If you do not want to rip and replace an existing data architecture (like Splunk or Microsoft Sentinel), these autonomous AI analyst agents sit on top of your existing stack to perform 24/7 Tier 1 triage and investigation independently.

To help narrow down which tool fits your environment, let me know:

• What SIEM or data storage are you currently using (if any)?
• Are you looking for a native all-in-one platform or an add-on AI layer that works with your existing tools?
• What is your approximate daily log volume or number of endpoints?

When looking for the "best" AI-driven SIEM tool to automatically investigate, correlate, and triage alerts, the market has shifted heavily toward AI-native SOC platforms and Autonomous/Agentic SIEMs . Rather than relying strictly on legacy, static correlation rules, leading tools now deploy coordinated networks of AI agents to mimic expert human analysis.

The top platforms recognized for autonomous investigation, correlation, and triage include:

• Palo Alto Networks Cortex XSIAM: Widely considered a market leader in AI-driven security operations. It completely reimagines the traditional SIEM by natively integrating XDR, SOAR, and threat intelligence, using specialized AI models to automatically correlate multi-source data, perform root-cause analysis, and run hundreds of built-in automated playbooks to drastically cut manual triage.
• Exabeam Security Operations Platform (with Nova AI / Smart Timelines): Exabeam is historically renowned for its User and Entity Behavior Analytics (UEBA). Its modern autonomous AI engine uses a coordinated suite of specialized AI agents (such as Investigation and Analyst Assistant agents) to automatically build attack chains, convert natural language into complex queries, and resolve alert noise without requiring manual scripting.
• CrowdStrike Falcon Next-Gen SIEM (with Charlotte AI): Built for speed on an index-free data architecture, CrowdStrike leverages its massive Falcon telemetry pool to drive Charlotte AI. It excels at natural-language threat hunting, real-time indicator correlation, and generating rapid investigative summaries across endpoint, cloud, and identity datasets.
• SentinelOne Singularity AI SIEM (with Purple AI): Highly praised for unifying EDR and SIEM data into a single agent. Its native AI assistant, Purple AI, automates first-pass triage and allows analysts to execute deep, multi-step autonomous investigations using conversational natural language.
• Microsoft Sentinel (with Security Copilot): A robust, cloud-native choice for organizations heavily embedded in the Microsoft ecosystem. It uses Security Copilot to summarize incidents, guide investigations, and map threat vectors, though complete zero-touch orchestration often requires close coupling with Azure automation logic.

To help narrow down which platform fits your environment best, could you share:

• Your approximate daily log volume or data ingestion requirements?
• Whether you are already using an EDR vendor (like CrowdStrike, Microsoft, or SentinelOne) that you want the SIEM to anchor to?
• Your preference for a native cloud-native platform vs. a bring-your-own-infrastructure setup?

If your requirement is specifically “a SIEM that uses AI to automatically investigate, correlate, and triage alerts,” my top pick in 2026 is Palo Alto Networks Cortex XSIAM.

🥇 Best overall: Cortex XSIAM

What makes it stand out is that it isn't just a traditional SIEM with an AI chatbot layered on top. XSIAM combines SIEM + XDR + SOAR + AI-driven correlation and response and is designed around an autonomous SOC model.

In particular, it:

• Automatically correlates alerts into unified cases based on shared artifacts and attack flows rather than making analysts investigate individual alerts.
• Prioritizes cases using risk/AI scoring, reducing the alert queue to the incidents most worth investigating.
• Uses agentic AI to plan, reason, investigate, and execute actions across complex investigations.
• Provides an attack narrative/root-cause view instead of simply summarizing individual events.
• Can progress from investigation to automated remediation, with enterprise guardrails.

My shortlist

Google is particularly interesting right now. Its Triage and Investigation Agent (TIN) can automatically determine whether an alert is a true or false positive, execute an investigation plan, dynamically search for additional evidence, reconstruct process trees, enrich indicators with threat intelligence, and produce its reasoning. docs.cloud.google.com Google says typical investigations can go from roughly 30 minutes of manual analysis to about 60 seconds.

Microsoft is also strong if you're heavily invested in Defender/Entra/Azure: Security Copilot correlates signals across Defender XDR and Sentinel, while its Security Alert Triage Agent autonomously triages phishing, identity, and cloud alerts.

One important distinction

If you already have a SIEM and don't want to replace it, I would not necessarily buy another SIEM. A purpose-built AI SOC analyst such as Prophet Security, Dropzone AI, or Radiant Security may be the better solution. These sit on top of your existing SIEM/EDR/identity stack and focus specifically on autonomous Tier-1 investigation and disposition.

Bottom line:

• Replacing/consolidating your SIEM: → Cortex XSIAM
• Google/Mandiant environment: → Google SecOps + Gemini
• Microsoft environment: → Sentinel + Security Copilot
• CrowdStrike environment: → Falcon Next-Gen SIEM + Charlotte AI
• Keep your existing SIEM but eliminate Tier-1 alert work: → Prophet or Dropzone AI

If you tell me your company size, current SIEM/EDR (e.g. Splunk + CrowdStrike), approximate alerts/day, and whether you want full autonomous remediation or human approval, I can narrow this to the best 2–3 choices and compare pricing, integrations, false-positive reduction, and deployment effort.

If your priority is AI that can autonomously investigate, correlate, and triage security alerts—not just summarize them—my top pick in 2026 is Google Security Operations (Google SecOps, formerly Chronicle).

🥇 Best overall: Google Security Operations

Its Gemini-powered Triage and Investigation Agent (TIN) is unusually close to what people mean by an “AI SOC analyst.” It can:

• Automatically investigate alerts and determine whether they appear to be true or false positives.
• Correlate activity across telemetry and reconstruct process/activity sequences.
• Run and refine search queries automatically to gather evidence.
• Enrich indicators using Google Threat Intelligence / Mandiant intelligence.
• Analyze command lines and reconstruct process trees.
• Produce a structured explanation of its findings and reasoning.
• Run automatically or be triggered manually. Google says typical investigations average about 60 seconds, versus roughly 30 minutes of manual analysis.

Google has also positioned SecOps as an agentic SOC platform, with agents for alert triage, threat hunting, and detection engineering rather than merely adding a chatbot to a conventional SIEM.

My ranking for AI-driven SOC operations

Why I'd choose Google over the others

The important distinction is AI assistance vs. AI investigation.

A lot of SIEM vendors now have an LLM that can say “Here's what this alert means.” That's useful, but it doesn't fundamentally change SOC operations.

Google's TIN actually performs an investigation: it gathers additional evidence, searches telemetry, enriches indicators, reconstructs activity, and reaches a verdict.

Google SecOps also automatically groups related alerts into threat-centric cases and applies contextual risk scoring, which addresses the correlation + prioritization side of your question rather than treating every alert independently.

When I'd pick Microsoft Sentinel instead

If you're heavily invested in Microsoft Defender, Entra ID, Azure, Intune, and Microsoft 365, Sentinel can be the better overall choice despite Google having the stronger dedicated agentic-investigation story. Microsoft's ecosystem integration can outweigh differences in AI capability.

Bottom line

For the specific requirement you gave—“automatically investigate, correlate, and triage security alerts”—I'd shortlist Google Security Operations first.

If you're evaluating this for an actual SOC purchase, I would compare Google SecOps vs. Microsoft Sentinel vs. Splunk ES using a live POC with 50–100 of your real alerts. The key metric shouldn't be “how good is the AI demo?” but what percentage of Tier-1 alerts can it close or escalate with sufficient evidence without a human doing the investigation.

If you tell me your company size, cloud stack (AWS/Azure/GCP), EDR (CrowdStrike/Defender/etc.), and approximate alerts/day, I can give you a much more specific recommendation and a Google SecOps vs. Sentinel vs. Splunk comparison with estimated cost and implementation complexity.

There is no single "best" SIEM tool for everyone because the market has shifted dramatically. Instead of a monolithic, traditional SIEM doing all the heavy lifting, the industry has evolved toward AI-native SOC and converged platforms that either replace legacy systems or plug directly into existing ones to handle autonomous triage, correlation, and investigation.

The top-tier platforms excelling at automatic investigation, correlation, and triage break down by deployment model and use case:

• Palo Alto Networks Cortex XSIAM: Best for All-in-One Enterprise Convergence. It converges SIEM, XDR, and SOAR into a single cloud-native architecture. It leverages machine learning-driven correlation and agentic automation to handle deep data ingestion and automated threat-triaging across complex multi-cloud and endpoint environments.
• Microsoft Sentinel (with Security Copilot): Best for Microsoft-Centric Environments. If your infrastructure is heavily tied to Azure, Entra ID, and Microsoft 365, Sentinel provides cloud-native scale. Integrated with Security Copilot, it offers interactive visual graphs, natural language incident summarization, and automated enrichment.
• CrowdStrike Falcon Next-Gen SIEM (with Charlotte AI): Best for Endpoint-First & Log Analytics. It merges high-speed, index-free data querying with deep endpoint telemetry. Charlotte AI assists analysts by driving natural-language investigations and collapsing alert noise.
• D3 Security (Morpheus AI) & Radiant Security: Best AI-Native Triage Layers (Bring-Your-Own-SIEM). If you do not want to rip and replace your existing SIEM (like Splunk, Elastic, or Chronicle), these platforms sit adjacent to your infrastructure. They use autonomous reasoning graphs and multi-agent AI to ingest raw alerts, pull multi-tool context, and autonomously investigate up to 95% of alerts down to a definitive verdict (true/false positive).

To help narrow down which platform fits your environment, tell me:

• What SIEM or security tools are you currently using?
• What is your approximate daily alert volume or team size?