Adding text normalization to a SIEM pipeline.
User-reported phishing emails, threat-intel text, and abuse inbox submissions are unstructured. This architecture inserts Sentiqra as the normalization layer before SIEM ingest - so routing happens on structured signals, not on an analyst reading every report.
Illustrative reference architecture. The scenario, volumes, and economics below are modeled - not a named customer case study. Validate every number against your own workload.
The scenario
A managed security provider (MSSP) operates a shared SOC for mid-market customers. Users at client organizations report suspicious emails to a central abuse inbox - tens of thousands of reports per day, in multiple languages. Today, analysts triage each report manually before it can be correlated with known campaigns or escalated into the SIEM. The queue grows faster than the team.
Before / after architecture
Before
With Sentiqra
Decision ownership stays with you
- Sentiqra produces signals. Your SOAR playbooks and escalation rules decide what happens next.
- Confidence thresholds, auto-triage rules, and escalation paths stay in your orchestration layer.
- Every successful analysis carries a configuration ID and fingerprint - the evidence trail survives the handoff to ticketing.
Illustrative economics
Both columns are modeled from explicit assumptions. Do not treat these as guaranteed savings - model them against your own workload.
Current approach (modeled)
- Analyst-minutes per reported email × reports/day × loaded analyst cost
- + dwell time while reports wait in the manual queue
- + missed-campaign cost when correlated reports surface late
With Sentiqra (modeled)
- N reports/day × 1 Cybersecurity analyzer run per report
- = N analyzer runs/day at current Sentiqra pricing
- Analyst time shifts to the prioritized queue tail - not the full stream
Model with your real report volume and analyst cost. The win is queue ordering, not analyst replacement. See current pricing.
Failure behavior
Enterprise architects care about what happens when analysis is unavailable almost as much as accuracy. Define these states explicitly.
Sentiqra available
Normal flow - signals route into SIEM/SOAR with confidence scores attached.
Analyzer latency spike
Reports buffer and process async - no report is dropped; triage order may lag.
Sentiqra unavailable
Fallback to the pre-existing manual queue. Explicitly defined, tested in drills.
Quota / spend cap reached
Explicit operational state - not silent failure. Overflow routes to the manual queue.
SIEM ingest failure
Sentiqra evidence is retained per request ID - re-ingest replays the same analysis.
Illustrative operational impact
Queue ordering, not queue removal
Analysts stop reading the reports that carry no threat signals. The stream they inspect is the tail, prioritized by confidence.
Correlation across clients
The same lure pattern reported at three client organizations surfaces as one campaign - because the signal codes match.
Evidence that survives the handoff
Configuration ID and fingerprint travel with the ticket. When a client asks why an email was escalated, the analysis replays.
What to measure in your evaluation
Run both approaches against the same labeled production sample. Compare:
The right migration decision should come from your workload - not a generic savings percentage.
Build the reference architecture
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