6mo → 1wk
Time to onboard a source
so the POC covers your real source mix
Fleak joins the Databricks startup accelerator. See the announcement
Evaluate SIEMs on your own data. Not on a vendor's demo.
Fleak forks your real production telemetry to two or three candidate SIEMs at once, each in its native format. The bake-off compares detection, search, and cost on identical events, and the incumbent never notices.
- Live production data
- Side-by-side POCs
- Native formats
- Cost modeling
- Zero impact on the incumbent
< 5 min
New source to OCSF
Zscaler and Okta onboarding in the Gruve benchmark
60–80%
SIEM ingest reduction
modeled into every candidate's price
Most SIEM evaluations measure
the demo, not your environment.
A proof of concept onboards three sources, runs the vendor's sample detections, and prices a volume nobody will actually send.
Three sources, not three hundred
Onboarding every source into every candidate takes months, so the POC tests the easy ones and the hard ones show up after the contract.
Different data, different answers
Each candidate ingests a different slice at a different time. Detection results can't be compared because the inputs weren't the same.
Pricing on raw volume
Quotes assume you send everything. Nobody models what each SIEM costs once the noise is routed somewhere cheaper.
One stream, every candidate,
evidence instead of slides.
Fleak collects each source once and forks it to every SIEM in the evaluation, so the decision rests on identical data and real numbers.
Fork live data to every candidate
Send the same production events to Splunk, Microsoft Sentinel, Google SecOps, Palo Alto XSIAM, CrowdStrike NG-SIEM, or Elastic at the same time.
Native format for each
Every candidate receives events in the schema its content expects, so out-of-the-box detections get a fair test.
Your full source mix
AI-generated parsers onboard the long tail in days, so the evaluation includes the custom apps and legacy devices that usually get left out.
Real cost per candidate
Measure the volume each candidate would ingest after filtering and routing, and price it at each vendor's real rate.
No impact on the incumbent
The current SIEM keeps receiving exactly what it receives today. Evaluations run in parallel and end without a cleanup project.
Keep the winning pipeline
The pipeline built for the POC becomes the production pipeline for the winner. The migration starts the day you sign.
Synthetic data generator
Simulate realistic attack and benign telemetry to test candidates on scenarios your environment hasn't produced yet, without exposing production data.
Masked during the test
Sensitive fields are masked before data reaches any candidate, so a POC never turns into a compliance exception.
An evaluation scorecard
Score every candidate on the same checklist: detections fired, search speed, onboarding effort, and modeled cost.
Decide on evidence.
Same events, every candidate, side by side. Then keep the pipeline for the winner.
A bake-off
in four steps.
01 / Pick the sources
Choose the sources your detections depend on, including the ones vendors struggle to parse.
02 / Fork to candidates
Add each candidate SIEM as a destination in its native format. The incumbent is untouched.
03 / Run your detections
Run your own detections and hunts on identical data in every platform and compare the results.
04 / Decide and migrate
Choose on detection quality and modeled cost, then promote the winner's pipeline to production.
The Brain maps once.
Every candidate gets the same events.
The Brain generates a mapping per candidate from the same samples. The Muscle forks every event deterministically, so differences in the results come from the platforms, not from the data.
Candidates
- Splunk
- Microsoft Sentinel
- Google SecOps
- Palo Alto XSIAM
- CrowdStrike NG-SIEM
- Elastic
Three SIEM candidates, one 30-day evaluation.
What does each one receive?
Incumbent
UntouchedKeeps receiving every source exactly as today. Nobody re-points a forwarder.
Candidates
Live dataEach gets the same production events in its own format, including the long-tail sources.
Scorecard
EvidenceDetection hits, search speed, and modeled cost per candidate, measured on identical data.
Run the evaluation on your data, at your volume, with your detections. Then keep the pipeline for whichever platform wins.
"A SIEM evaluation is only as good as the data you feed it. Feed every candidate the same events, and the decision makes itself."
SIEM evaluation · Fleak Platform
Bring your shortlist.
30-minute working session. We'll show one source landing in every candidate's format.
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