01 — Problem
The friction
Alert fatigue hides real incidents inside endless false positives.
OpsGuard
OpsGuard sits beside the SOC — triaging alerts, summarizing threats, and opening the right playbook so responders act with context instead of noise.
- Noise filtered
- 72%
- Time to assess
- −45%
- Alerts per case
- 40 → 1
Demo
See it in motion
A short walkthrough of the agent loop — from signal in to decision out.
Demo reel
Alert triage to playbook
Overview
Case at a glance
Target users: SOC analysts, detection engineers, and incident commanders.
02 — Solution
The approach
A SOC co-pilot that correlates alerts, enriches them with identity and asset context, writes the threat narrative, and opens the matching playbook.
03 — Value
Why it matters
Less noise, faster understanding, and cleaner handoffs during incidents.
How it works
The agent loop
From raw signal to a decision OpsGuard can defend.
- 01
Correlate
Groups related alerts into a single candidate incident instead of forty separate tickets.
- 02
Enrich
Adds identity, asset criticality, and threat intel context around every event in the group.
- 03
Narrate
Writes the timeline an analyst can brief from, naming the one event that actually matters.
- 04
Hand off
Opens the matching playbook with prepared next steps that still require human approval.
Capabilities
What OpsGuard actually does
Built for SOC analysts, detection engineers, and incident commanders.
- 01
Alert enrichment
Correlates identity, asset, and threat intel around each noisy alert.
- 02
Threat narratives
Turns raw events into a timeline analysts can brief on immediately.
- 03
Playbook launch
Opens the right response path with suggested next actions.
- 04
Post-incident notes
Drafts what happened, what worked, and which detections to tune next.
Architecture
How the system thinks
Data flows left to right: sources feed the orchestrator, specialists reason in parallel, tools execute, and one artifact comes out.
Sources
- DataSIEM alerts
- DataThreat intel
- DataAsset inventory
Orchestration
- OrchestratorSOC orchestrator
- LLMReasoning LLM
Specialists
- AgentTriage agent
- AgentIR agent
Tools & output
- ToolEnrichment
- ToolPlaybooks
- OutputIncident brief
- Data
- Orchestrator
- LLM
- Agent
- Tool
- Output
In action
A real exchange
An abbreviated conversation, close to what the agent actually returns.
OpsGuard Session active
- You
What is behind the 40 alerts on host WEB-07?
- OpsGuard
One story, not forty: a credential-stuffing burst from a single ASN, all failed, followed by one successful login from the same range at 02:14. That last event is the one that matters.
- You
Contain it?
- OpsGuard
I can stage host isolation and token revocation, but execution needs your approval — I do not act on production systems.
Design decisions
Trade-offs worth naming
The constraints that shaped the system — and what was deliberately left out.
- 01
Read-only by default
The agent never executes containment. It prepares the action so a responder approves it in one step.
- 02
One narrative per incident
Correlation happens before summarization, so analysts read a single story rather than forty fragments.
- 03
Detections stay owned by engineers
The agent suggests tuning but never edits detection rules, keeping the detection pipeline auditable.
Honest limits
Where it stops, where it goes
What the agent does not handle today, and what comes next.
Current limitations
- Depends on log coverage — blind spots stay blind.
- Novel attack patterns still need analyst intuition.
- No automated containment.
On the roadmap
- Detection tuning suggestions with impact estimates
- Purple-team scenario replay
- Approval-gated containment actions
Stack
Technology
Nothing added without a concrete requirement behind it.
PythonLangGraphOpenAIElasticNuxt