AI alert triage that works inside your SIEM and EDR. It pulls context, collapses duplicates into incidents and writes a verdict an analyst can check in seconds. Response actions stay behind your approval rules.
AI alert triage is the automated first-level review of security alerts from SIEM, EDR and cloud tools. An AI agent enriches each alert with identity, asset and threat-intelligence context, groups related alerts into one incident and assigns a verdict such as benign, suspicious or malicious. It outputs the verdict, the queries and evidence behind it, and a recommended next step for a human analyst.
Most SOCs add detections faster than they add people. Alerts arrive without context, duplicates pile up, and the queue decides what gets looked at.
of alerts in in-house SOCs were false positives, and 53% at MSSPs, in a 2021 IDC survey of 300 US SOCs and 50 MSSPs.[2]
security analysts and managers ignore alerts when queues are full, according to the same IDC survey.[2]
Mean time to identify and contain a breach in 2025, per IBM's Cost of a Data Breach report.[1]
Enrichment and a verdict before an analyst opens the alert, with the exact queries shown so it can be checked.
Each alert is expanded with the facts an analyst would look up first, using read-only API access to your tools.
Alerts from different tools that share a user, host or indicator are merged into one incident with a timeline.
The agent follows your runbooks, runs investigation queries and writes a verdict with the evidence attached.
We connect to your SIEM, EDR and identity tools with read-only service accounts, choose the top 10–15 noisiest detection rules and agree one metric: analyst-touched alerts or mean time to triage.
The agent re-triages 30–60 days of closed alerts. We compare its verdicts with your analysts' dispositions and review every case where it would have closed a true positive.
Verdicts are written as comments in your case system while analysts work as normal. Disagreements feed runbook and prompt fixes.
Auto-close is enabled only for rules with no missed true positives in testing, with random sampling. We report the metric and the Run plan.
| Criterion | Manual tier-1 triage | Built-in SIEM/XDR AI assistant | Stratgik build + run |
|---|---|---|---|
| Coverage across tools | Analyst pivots between consoles | Strongest inside that vendor's own stack | Splunk, Sentinel, CrowdStrike, Defender, Okta and ticketing together |
| Uses your runbooks | Yes, unevenly followed | Generic guidance | Your runbooks and allow-lists encoded and versioned |
| Evidence for each verdict | Case notes vary | Summaries, partial query visibility | Every query, result and reasoning step stored |
| Automated response | Manual | Available, vendor-scoped | Via your SOAR with human approval rules per action |
| Multi-tenant (MSSP) | Manual context switching | Depends on licensing | Per-client runbooks, data separation and reporting |
| Best fit | Low alert volume | Single-vendor environments | Mixed stacks and MSSPs with many tenants |
Faster identification and containment reduces what an incident costs. AI in the SOC pays off when it is measured on missed detections as well as saved minutes.
Estimate analyst hours released when routine alerts arrive already enriched and resolved with evidence. The share resolved without analyst effort is an assumption; the pilot measures it rule by rule.
Illustrative estimate using your inputs and stated assumptions, not a quote or guarantee. The pilot measures the real figure against your baseline.
One SIEM or XDR, up to 15 detection rules, one environment or tenant
24/7 operation, tuning and weekly accuracy review
More tools, rules, tenants and approved response actions
Model usage, SIEM query costs and cloud hosting billed at cost. Stratgik does not replace your incident response retainer or accountability for security decisions. Taxes excluded. GBP and AED prices are indicative conversions from USD.
AI alert triage accuracy depends on your data and runbooks, so it must be measured on your alerts before anything is auto-closed. In our pilot the agent re-triages 30–60 days of closed alerts and we count every true positive it would have dismissed. Auto-close is enabled only for rules where that number is zero, and live verdicts are sampled by analysts every week.
Yes. The agent uses the platforms' APIs to run SPL in Splunk, KQL in Sentinel and Falcon queries in CrowdStrike, and reads context from Entra ID, Okta, Defender, ServiceNow and threat-intelligence feeds. It writes verdicts back as comments or fields in your existing case management, so analysts do not need a new console.
Only if you allow it, per action. By default the agent is read-only and proposes actions such as isolating a host, revoking a session or disabling a user. Those run through your SOAR playbooks with analyst approval. Some teams later allow low-impact actions, like blocking a known-bad hash, to run automatically with notification.
SOAR playbooks follow fixed branches, which works for predictable alerts but breaks when context is missing or unusual. An AI triage agent decides which lookups to run, reads the results and reasons about them, then records its steps. We use both: the agent investigates and recommends, and your SOAR executes approved actions reliably.
Stratgik's pilot is a fixed $18,000 for one SIEM or XDR and up to 15 detection rules. Run is $5,000 a month including tuning and accuracy reviews. Scale for multiple tenants, more tools and approved response actions starts from $12,000 a month. Model and query usage is billed at cost.
It stays in your environment. The agent runs in your AWS, Azure or GCP account, uses read-only service accounts, and calls model endpoints that do not retain or train on your data. For MSSPs, each client tenant has separate credentials, runbooks and storage. Every query and model call is logged for audit.
We will show you, on a sample of your own closed alerts, how the agent would have triaged them and where it would have needed a human.