Fleak joins the Databricks startup accelerator. See the announcement

Less volume. Same coverage.

Fleak filters noise, trims bloated fields, suppresses duplicates, and samples or aggregates high-volume telemetry in flight. The Brain shows which event types never fire a detection, and your team decides what to cut.

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  • Filtering
  • Field trimming
  • Deduplication
  • Sampling
  • Logs to metrics
  • AI-suggested cuts

60–80%

SIEM ingest reduction

signal-worthy event types only

50%+

Guaranteed minimum savings

on SIEM ingest, with no drop in detection coverage

14 days

Guaranteed time to value

from deployment to measured SIEM savings

Most of what you ingest
never fires a detection.

Successful logins, routine DNS, health checks, and verbose debug fields fill the SIEM at hot-path prices.

Bloated events

Identity and cloud audit events carry kilobytes of fields no rule reads: debug context, request echoes, nested metadata.

Duplicates billed twice

The same alert from two agents, the same event re-sent by a forwarder. Every copy is ingested and paid for.

Cutting blind

Teams drop whole sources to hit a budget and find the blind spot during an incident.

Cut the noise,
keep every signal.

Every reduction runs in flight, before the SIEM's ingest meter sees a byte, and every rule is reviewed before it ships.

Filter by event type

Drop event types no detection, hunt, or report uses, with filters on any field, value, or expression.

Trim fields

Remove empty, null, duplicated, and unused fields from every event, so what's left is the part detections read.

Deduplicate at ingestion

Suppress repeated events by key, such as one alert per host per minute, and keep a count of what was dropped.

Sample and aggregate

Keep 1 in N of high-volume, low-value events with dynamic rates, or roll them up into metrics, tagged so counts scale back up.

AI-suggested cuts

The Brain profiles your sources, shows which fields and event types never reach a detection, and keeps suggesting cuts as it learns how your team uses the data. You approve every cut.

Savings you can show

See volume in and out for every pipeline and destination, priced at your contracted rate. For most teams, SIEM savings cover the cost of Fleak within the first quarter.

Prebuilt reduction rules

Start from a library of security-specific reduction rules for firewalls, EDR, DNS, and cloud audit logs, then tune them to your environment.

Detection-safe by design

Before a filter ships, Fleak checks it against your SIEM's active detection rules, so no event or field a rule depends on is dropped.

Forecast the bill

Project data growth and cost per destination, and see the effect of every rule before your next renewal.

Your SIEM bill is a noise tax.

Stop paying it on events nobody acts on. Everything you cut still lands somewhere you can query.

Read the docs Book a demo

The Brain finds the noise.
The Muscle drops it.

The Brain profiles fields and event types across your sources and proposes what to filter, trim, sample, or aggregate. The Muscle applies the approved rules deterministically in flight, and the full-fidelity copy goes to cheap storage.

Works in front of

  • Splunk
  • Microsoft Sentinel
  • Palo Alto XSIAM
  • Google SecOps
  • Datadog
  • Elastic

Ten million successful VPN logins a day.
Which ones does the SIEM need?

Before

All ingested

Every success event, every field, at SIEM prices. No detection reads them.

After

Signal only

Failures and anomalies go to the SIEM. Successes roll up into metrics, and the raw events go to the lake.

Trust model

Approved

Every filter is reviewed before deploy. Nothing a detection depends on is dropped.

Cut the volume, not the coverage. Everything you stop sending to the SIEM still lands somewhere you can query.

"Your SIEM bill is a noise tax. Most of what you ingest never fires a detection, and you pay hot-path prices for all of it."

Log reduction · Fleak Platform

Bring your SIEM renewal quote.

30-minute working session. We'll show which event types earn their seat and what the rest costs you.

Read the docs Book a demo

Explore Related

Replay

Store it cheap, replay it when it matters

A full-fidelity archive, replayed through the same pipeline.

See Detail →
Detection

Catch the known-bad before it's indexed

Sigma rules and ATT&CK coverage on normalized events.

See Detail →
Investigations

Investigate without rehydrating

One search across the lake, the archive, and the SIEM.

See Detail →