Best AI for SOC Analysts

Working a SOC shift is different from most knowledge work. The pressure is real-time. Alerts come in continuously, each one potentially significant, most of them false positives, some of them the beginning of something serious. The documentation requirements exist for legitimate reasons, audit trails, incident records, post-incident analysis, but they compete directly with the speed the environment demands.

Most AI productivity tools are designed for people who have blocks of uninterrupted time to work with them. SOC analysts don't have that. The tools that actually get used in a SOC are the ones that fit into fast, context-switching workflows rather than asking analysts to slow down and engage with a tool thoughtfully.

This guide covers three tools that fit that constraint. They're not trying to replace SIEM platforms, SOAR solutions, or threat intelligence platforms. They handle the written and research work that surrounds detection and response.

The time problem in a SOC

The documentation debt is real and it compounds. During high-volume shifts, incident records get brief because there's no time to write. Post-incident reports get delayed because the shift is still going. Runbooks don't get updated because updating documentation isn't as urgent as responding to the next alert.

This creates specific problems: analysts reviewing an incident a week later don't have the context to understand what happened, and new analysts joining the team don't have well-documented procedures to follow. Both problems affect detection quality over time.

AI helps most when it reduces the time cost of writing to the point where documentation actually happens during the shift rather than getting deferred. A draft incident note that takes thirty seconds to review is more likely to get written than one that takes ten minutes to write from scratch.

1. Claude (claude.ai)

Claude is the tool most SOC analysts actually use for the written work: incident documentation, investigation summaries, threat analysis write-ups, and stakeholder communication during active incidents.

The incident documentation use case is the most direct. During or after triage, an analyst has mental notes about what they saw, what they investigated, what they concluded, and what action was taken. Claude converts rough notes into a structured incident record in the format your team uses. Give it the notes and the format you need, whether that's a Jira ticket structure, a specific post-incident report template, or a free-form investigation summary, and it produces a draft that the analyst reviews and submits.

For analysts who handle escalation communications, Claude drafts the technical summary going to tier 3 or to the incident commander, including the evidence gathered, the current working hypothesis, and what additional context would help. These communications have to be accurate and fast; Claude's drafting speed reduces the time between "I know what's happening" and "I've communicated it clearly."

Alert analysis write-ups are another common use case. When an alert requires a decision and documentation of that decision, Claude helps structure the analysis: what the alert triggered on, what the investigation found, what the conclusion is, and why. For analysts managing volume across a shift, having a structured template they can fill in quickly and then ask Claude to smooth into professional documentation reduces the per-alert documentation time.

One important caveat: don't paste active IOCs, internal system hostnames, IP addresses, or sensitive incident data into Claude's consumer tier. Use Claude for drafting from sanitized or synthetic notes, and keep the actual investigative data in your SIEM and case management tools. This is the difference between using AI to help with the writing and using it as a data processing layer for sensitive security information.

Best for: Incident documentation, investigation summaries, escalation communications, and written analysis during and after security incidents. Pricing: Free tier available; Claude Pro at $20/month.

2. Perplexity

Perplexity fills the research gap that comes up constantly in SOC investigations: you're seeing indicators or behaviors that look like something you've read about, and you need current public information about it quickly.

The practical scenario: you're investigating an alert that shows a specific tool being executed in an unusual way, and you need to know whether this execution pattern matches known threat actor TTPs in public reporting. Perplexity surfaces relevant MITRE ATT&CK references, recent threat reports from public sources, and public CVE advisories that might be relevant. It cites the sources, so you can go directly to the original report if you need more detail.

For CVE research during incidents, Perplexity is faster than navigating to NIST NVD, CISA, or vendor advisory pages individually. "What's the CVSS score and exploitability status of CVE-2025-XXXXX, and has CISA issued guidance on it?" produces a useful summary in seconds.

Perplexity is also useful for initial research on threat actor groups. CISA advisories, FBI flash alerts, and public threat intelligence reports are all indexed. If you're investigating something that has the characteristics of a known campaign, Perplexity helps you check whether there's public reporting on it before you spend time developing an attribution hypothesis from scratch.

The limit is what it always is with Perplexity: public sources only. Your internal IOCs, your specific environment details, and your active investigation context don't belong in a Perplexity query. Use it for external context, not as an analysis layer for operational data.

Best for: CVE research, threat actor TTP lookup, CISA advisory summaries, and quick context gathering from public threat intelligence sources. Pricing: Free tier available; Perplexity Pro at $20/month.

3. Glean

Glean addresses the institutional knowledge problem in mature SOC environments. The longer a security operations team has been running, the more valuable its accumulated knowledge becomes, and the harder that knowledge typically is to find.

Consider a real scenario: an analyst is investigating an alert that looks similar to something the team dealt with nine months ago. That past investigation is in Jira. The runbook that was updated after the incident is in Confluence. The email thread with the infrastructure team about the changes made during remediation is in Gmail. Without Glean, finding all of that context requires navigating three different tools and doing multiple searches. With Glean, one natural-language query surfaces all of it.

For shift handoffs, Glean makes it faster to get context on what happened before your shift and what's in progress. For new team members, it makes the team's documented institutional knowledge actually accessible rather than requiring weeks of informal knowledge transfer.

The detection playbook and runbook use case is where Glean adds the most daily value. When an alert type appears that an analyst hasn't worked before, Glean finds the relevant runbook, any past incidents of the same type, and any related documentation about the systems involved. That's seconds of context gathering instead of minutes of hunting through a wiki.

Glean is enterprise software with security controls appropriate for sensitive organizational information. The permissions model means analysts see documents they're authorized to access and nothing beyond that. For a SOC that takes access controls seriously, that's the right behavior.

Best for: Finding past incident records, detection runbooks, and institutional SOC knowledge across enterprise documentation systems. Pricing: Enterprise only; custom pricing.

Integrating these tools without slowing down

The analysts who get the most out of these tools have clear use cases in mind rather than using them exploratorily during a shift.

Before a shift: Use Claude to review and update documentation that came out of the previous shift. Use Perplexity to check for new advisories or threat intel relevant to active campaigns you're tracking.

During a shift: Claude for quick draft incident notes and escalation communications. Perplexity for fast lookup of public CVEs and threat actor context when an alert shows patterns worth checking against public reporting.

After a shift: Claude for post-incident reports and runbook updates. Glean for finding past incidents to reference in the write-up.

The tools that try to integrate directly into SIEM platforms or replace SOAR workflows are a different category. These three are best thought of as writing and research tools that fit around the security platforms you're already using.

Frequently asked questions

Can Claude help with MITRE ATT&CK mapping in incident documentation?

Yes. If you describe the behaviors observed in an incident, Claude maps them to likely ATT&CK technique IDs and provides the reasoning. This is useful for structuring incident reports and for consistent technique tagging in your case management system. Always verify the mapping against the MITRE ATT&CK framework directly before finalizing documentation.

What about using AI for SOAR playbook development?

Claude Code is the better tool for that use case. Writing Python-based SOAR playbooks, building detection logic, and scripting response automation are coding tasks where Claude Code's file-aware agent is more useful than the chat interface. The use cases in this guide are for operational SOC analysts; SOAR development is more of an engineering function.

How do these tools compare to purpose-built security copilots like Microsoft Security Copilot?

Purpose-built security AI integrates directly with your security stack and can access your actual alerts, logs, and telemetry. The tools in this guide don't have that integration. The advantage of the tools here is cost and flexibility: $20/month vs. enterprise security copilot pricing, and they work for the writing and research tasks that security copilots don't always cover well. Many SOC teams use both.