Todaytrace AI

An AI assistant for SOC teams that triages and investigates SIEM alerts, summarizes what happened, maps it to MITRE ATT&CK and suggests a response, with the analyst making the call.

A system we build for organizations
SecurityAI AgentCloud Native
From the running system
The Todaytrace AI triage queue: cases ranked by risk score, a critical Suspicious authentication chain case scored 92 out of 100, raw logs pre-filtered and PII-masked before the AI, user and host context, the AI summary, MITRE ATT&CK mapping, a true-positive verdict at 88% confidence, and suggested responses
A screen from a system we built. Names of people and organizations have been replaced with sample data.
The problem

The SIEM raises more alerts than the team can read. Analysts go through raw logs line by line, gather context from several tools, and the alerts that matter get lost in the noise.

The outcome

Alerts are filtered and deduplicated before they reach people. Each case arrives with a summary, a risk score, user and host context, and a suggested response you can check.

Who it is for

SOC teams

You want less time on triage and more on the cases that matter.

Organizations with a SIEM

It connects to the SIEM you already run, whichever vendor it is.

Organizations without a SIEM

Start with Wazuh, an open-source SIEM we provide and run.

How it works

  1. Ingest from the SIEMEvents come from the SIEM you run, such as QRadar or Wazuh
  2. Filter and deduplicateThe pipeline drops noise, merges repeated events and scores anomalies before a case is opened
  3. Mask before the AIPersonal data in the logs is masked before it reaches the model
  4. AI assistSummary, MITRE ATT&CK mapping, a verdict with its confidence, and a suggested response
  5. The analyst decidesConfirm or correct the result; the feedback goes back into tuning the model

Capabilities

Risk-ranked triage queue

Cases ranked by a 0–100 risk score, filtered by severity and owner

AI summary and verdict

What happened, in plain words, with a verdict and its confidence

MITRE ATT&CK mapping

Behavior in each case mapped to ATT&CK techniques

Context in one place

User, host, asset criticality, source location and a deduplicated timeline

Suggested response

Such as disabling an account, blocking an IP or isolating a host; what runs automatically is set in action rules

Rules and tuning

Detection rules, pipeline tuning, model feedback and threat hunting

Measured

What we measure with you

Targets are agreed during Discovery, and real results are reported after the pilot.

  • KPI 1Time to triage per alert
  • KPI 2Share of alerts filtered before reaching an analyst
  • KPI 3Analyst agreement with AI verdicts
Your data, your control

Deployment options

Who operates itWhere data livesBest for
Managed cloudWe operate everythingA region you chooseFastest start, no infrastructure team needed
Your cloudWe deploy into your cloud accountStays in your accountOrganizations with an existing cloud policy
On-premiseInstalled in your data centerNever leaves your premisesData with the strictest requirements
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