Automate alert classification, logging, and downstream actions for SOC teams.
The AI agent reads the latest endpoint alerts from Google Sheets and standardizes the data fields. It sends the structured data to the GPT-4 model to produce a concise, structured JSON including a severity tag and an action recommendation. The agent logs the results to a centralized incident sheet and can trigger downstream EDR actions or alert notifications when configured.
End-to-end classification and logging to support SOC triage.
Ingests alerts from Google Sheets and maps fields to a consistent schema.
Sends the payload to the GPT-4 model for classification.
Returns a structured JSON with severity and recommended action.
Logs the results to a centralized incident sheet.
Optionally triggers automated actions or notifications.
Supports tuning risk thresholds and playbook routing.
Before, alert classification was inconsistent and triage was manual, causing delays and mis-prioritization. After, you get consistent severity tagging, automated triage with clear next steps, centralized logs for audits, an auditable history of decisions, and ready-to-act outputs for downstream tools.
A simple 3-step system flow anyone can follow.
Reads alerts from Google Sheets and maps hostname, IP, and risk score into a consistent dataset.
Sends the prepared payload to the OpenAI GPT-4 model and requests a structured JSON with severity and an action recommendation.
Writes the classification to the centralized incident sheet and optionally triggers EDR actions or incident notifications.
A realistic run-through of processing alerts.
Scenario: In a 60-minute window, the AI agent processes 20 endpoint alerts pulled from Google Sheets. For each alert, GPT-4 returns a severity (Low/Medium/High/Critical) and an action (Monitor/Investigate/Isolate/Escalate). The results are logged to the centralized incident sheet, and high-severity items trigger optional containment actions or alerts to on-call responders.
Key roles that gain from automated incident classification.
Delivers fast, consistent classifications and clear next steps for incident response.
Gains visibility into triage quality and an auditable workflow for audits.
Receives prioritized actions to containment and investigation.
Monitors SOC throughput and ensures standardized triage across teams.
Uses structured incident data to correlate alerts and enrich investigations.
Automates routine actions and reduces manual alert handling.
Core tools connected to the AI agent and what they do inside each.
Reads new alerts from the input sheet and writes classified results to the log sheet.
Produces a structured JSON with severity and action recommendations.
Runs the AI agent at defined intervals to process new alerts.
Can trigger containment actions or notify on-call based on severity.
Provides secure access to Sheets and APIs used by the agent.
Practical scenarios where the AI agent adds real value.
Common questions and practical answers.
GPT-4 is the recommended model for higher accuracy and richer reasoning, but the AI agent can be configured to use GPT-3.5 or other LLMs via API. The core contract is to return a structured JSON so the downstream steps remain consistent, regardless of the model. You can switch models to balance cost and latency, though results may vary in nuance.
It reads hostname, IP address, and risk score from the input sheet. Additional fields can be included and mapped to the standardized payload. The agent relies on a defined schema to ensure consistent classification, regardless of the source row order.
Yes. The agent can trigger EDR containment actions or alert notifications based on the severity and playbook routing. You can define which actions run automatically and which require human confirmation. This enables faster containment for high-severity incidents while preserving control for lower-risk alerts.
Yes. You can route incidents to different playbooks based on severity, asset type, or business impact. Each playbook can specify distinct containment, investigation, and escalation steps. This keeps responses aligned with organizational policies without manual reconfiguration.
Data remains under your control in Sheets and the central incident log. Access is managed via your standard OAuth2 credentials and IAM/security controls. Where logs are stored, and how long they’re retained, should follow your organizational data governance policies.
Tune the GPT prompt or risk thresholds in the classification node to reflect your risk appetite. After updating, you may need to re-run or reload the Cron/Webhook to apply new settings. The system supports per-field thresholds to balance false positives and missed high-severity alerts.
Yes. You can swap Google Sheets for Supabase, Airtable, or a database, with the integration adjusted to feed alerts into the same classification flow. The core logic remains: ingest, classify, and log. You’ll need to reconfigure the input and log endpoints accordingly.
Automate alert classification, logging, and downstream actions for SOC teams.
