SIEM implementation
From log collection to working alerts: ingestion, correlation, tuning until the noise is gone.
A SIEM that alerts on everything is functionally the same as a SIEM that alerts on nothing: real signals get lost in noise within a week. We implement SIEM from sizing and log ingestion through parsing, normalisation and correlation rules, then spend the time most implementations skip: tuning, until what fires is worth an analyst's attention.
How it runs
- 1
Size for the log volume you actually have
Over-provisioning wastes budget, under-provisioning drops logs silently; we size against real, measured volume.
- 2
Ingest and normalise properly
Logs from different sources are parsed into a consistent format, so correlation rules can actually compare them.
- 3
Write correlation rules for real patterns
Rules are built around attack techniques relevant to your environment, not copied wholesale from vendor content.
- 4
Tune until it is usable
We iterate on alert thresholds until the volume an analyst sees is something they can sustainably act on, not drown in.
Common questions
Which SIEM platforms do you work with?
How long until alerts are actually useful?
Can you tune a SIEM we already have, without a full rebuild?
Tell us what you need.
One paragraph is enough. You'll get a straight answer on whether it's a fit, roughly what it takes, and what happens next.