60–80%
SIEM ingest reduction
signal-worthy event types only
Most of what you're ingesting has no detection value. Fleak routes only what earns its seat — before it hits your ingest meter.
60–80%
SIEM ingest reduction
signal-worthy event types only
< 5 min
Any new log source
seen or unseen — routing with correct intention
T1 → T3
Detection fidelity uplift
same model — intention-aligned inputs
SIEM pricing is volume-based. Log volume grows 30–100% per year. Most of that growth has no detection value — but it all hits your ingest meter.
Successful logins, routine DNS queries, benign CloudTrail API calls, bulk EDR telemetry — high-volume event types your analysts have never fired an alert on, ingested at full SIEM price every day.
A filter that works for one team's use case silently damages another team's compliance posture. And every upstream schema change turns static filters into incidents.
Drop sources to stay on budget and accept blind spots. Or pay the full bill and lose the argument with finance next quarter. There should be a third option.
Every event type evaluated against your downstream security
intention.
What belongs in your SIEM. What belongs in your data lake. What belongs
nowhere.
Your SIEM doesn't care what a log means. It just bills you for it. Fleak evaluates every event type against what your downstream tools actually need — and routes accordingly. Signal to your SIEM. Compliance to your lake. Noise to nowhere.
works with any SIEM
Windows Event 4625 — failed logon.
One event type. Three correct answers.
Threat Intel Platform
All → SIEMCorrelates every failure against live threat feeds. One failure from a known-bad IP is Tier 1 signal. A count-based drop filter destroys core detection value.
Financial SOC
All → LakeSOX mandate: retain every failed logon 90 days. Dropping any event is a compliance violation — not a cost optimization.
Lean Startup SOC
Burst OnlyTwo analysts, no mandate. Only burst patterns matter — 10+ failures in 60s. Everything else is noise they can't act on.
Hard-coded filters can only serve one of them. Fleak serves all three — simultaneously, without conflict.
"With Fleak-normalized data, our AI agent stopped grinding through parsing and moved straight to high-fidelity analysis. Same model. Tier 3 detection fidelity. No extra cost."
Enterprise Security Customer · Global Deployment (Anonymized)
Bring your SIEM renewal quote and a log source that's been giving you trouble.
Your pipelines didn't fail. They just went quietly wrong.
See Detail →Alert fatigue isn't a volume problem.
See Detail →Your AI agent is doing data engineering in its context window.
See Detail →