Your AI SOC is only as good as the data it can reach

Realm sits upstream of your SIEM, your lake, and your agents, and lands every event in your lake parsed, enriched, and ready to query. Your agents work on it the day it lands, with no data engineering project first.

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Every source, one shape

Most AI SOC projects stall on the data, not the agent

Agents are taking on the work of the SOC, from triaging every alert at machine speed, to investigating, to hunting. Every one of those workflows is bounded by the data the agent can reach, and the shape it arrives in.

Point an agent at a lake today and it finds raw vendor log, one long string per event, different for every source. Before the agent can do anything, someone has to parse it, map it, and keep that mapping alive through every new source and schema change. That is a data engineering project, and it is usually where the AI use case dies.

An agent cannot reason over a field it cannot read, or recover one that was never collected. What your AI SOC can do is decided upstream.

What lands in your lake

The same firewall event and the same agent question. Today it lands as raw vendor log with nothing to query. With Realm upstream, it lands in Realm lake format, with the raw event intact and the parsed fields, observables, metadata, and enrichments beside it.

What lands today
Palo Alto firewall event

1,2026/09/18 14:02:11,013201009832,TRAFFIC,end,2561,2026/09/18 14:02:11,10.4.12.37,203.0.113.45,198.51.100.10,203.0.113.45,allow-web-out,corp\jsmith,,ssl,vsys1,trust,untrust,ethernet1/2,ethernet1/1,fwd-lake,2026/09/18 14:02:11,418822,1,52144,443,41022,443,0x400053,tcp,allow,6412,1832,4580,18,2026/09/18 14:01:58,12,any,0,7302118834,0x0,10.0.0.0-10.255.255.255,DE,0,11,7,tcp-fin,16,0,0,0,,fw-edge-01,from-policy,,,0,,0,,N/A,0,0,0,0,1,2026/09/18 14:02:12,013201009832,TRAFFIC,end,2561,2026/09/18 14:02:12,10.4.12.52,198.51.100.23,198.51.100.10,198.51.100.23,allow-web-out,corp\\amurphy,,web-browsing,vsys1,trust,untrust,ethernet1/2,ethernet1/1,fwd-lake

Agent asksWhich internal hosts talked to 203.0.113.45, and is it malicious?
Nothing to query. Parse it first.
What lands with Realm
Same event, Realm lake format
raw
1,2026/09/18 14:02:11,013201009832,TRAFFIC,end,...
parsed
src_ip10.4.12.37actionallow
observables
ip203.0.113.45userjsmith
metadata
sourcepalo_alto
enrichments
threat_inteltor_exit
Agent asksWhich internal hosts talked to 203.0.113.45, and is it malicious?
10.4.12.37, user jsmith. The destination is a known Tor exit.

Same event, same question. One needs a parsing project first, the other is ready the day it lands.

See this on one of your own logs. Book a 30-minute session 

Data prepared for the agents that read it

Realm lake format is how data leaves Realm ready for agents.

01

Collect once

Realm collects from every source and understands what each one contains, field by field.

02

Shape in stream

Reduce, enrich, redact, and normalize on rules your team approves, with the reasoning shown.

03

Land as one record

Every event lands as one consistent record: the raw log, the parsed fields, the observables, the metadata, and the enrichments.

04

Put an agent on it

There is no normalization project first: your team can put an agent on it the day it lands, not six months later.

Already have a data engineering team?

Then you know what it costs to keep this running. Every new source, every vendor schema change, and every broken parser is their time, competing with the rest of the business. Realm takes on the upkeep, so that team works on what is unique to you.

Your SIEM and your lake want opposite things

A pipeline that only moves data sends the same shape everywhere. Realm decides what each destination needs and produces it, off the same source feed.

Your SIEM
Needs
Lean, parseable, detection-relevant data. Noise costs money.
Realm sends
The leanest input that still fires every detection.
You get
Lower ingest cost, with no detection gaps.
Your lake
Needs
Structure and context that join across sources, without owning the parsing.
Realm sends
Every event in Realm lake format, with the raw event intact.
You get
Data an agent can reason over the day it lands.

The same pipeline that cuts your SIEM bill feeds your lake data your agents can use.

What else your AI SOC gets from Realm

Enrichment

Context for faster verdicts

Realm attaches IP intelligence and commercial threat intelligence while data is still in stream. Events arrive carrying the context an agent would otherwise assemble mid-investigation, so verdicts come faster and fewer end inconclusive.

Detection Integrity

The full picture, protected

Before any reduction ships, Realm checks it against the detections you run and protects the fields they depend on, mapped to MITRE ATT&CK. Nothing your AI SOC works from goes silently missing.

Explore Detection Integrity

Bring your own agent

Your lake, your agent, your model

Realm feeds the lake and the agents you already chose, it does not replace them. Records land as open JSON, destination-agnostic, so nothing is locked to us.

Watch an agent hunt ransomware, live

Our security and AI experts run a live threat hunt with Claude on Realm-optimized data in Databricks, starting from nothing but a CISA advisory and a table name.

  • A working session with our security and AI experts, not a sales pitch
  • A real hunt across email, firewall, and Windows logs
  • Nothing to install and no data to share
Book Your 30-Minute Threat Hunt

Want it on your own logs? We run that next.

Proof, in production

Global manufacturer

One of the largest Microsoft Sentinel deployments in the world.

Their own agents now run on firewall data in their lake, with no data engineering project in between.

They came to Realm to cut a Sentinel bill, and chose Realm over other pipelines for reduction effectiveness and a modern, fully managed architecture. The same firewall data Realm trims for Sentinel now also lands in their lake in Realm lake format, off the same pipeline.

Why they bought

3×return per $1 spent on Realm
1,000+KQL rules replaced in 72 hours
>50%reduction of Palo Alto logs

Go deeper

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Your agentic SOC is only as good as the data it can reach.

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Agentic defense is only as strong as the data it reads.

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Your AI SOC is only as good as the data it can reach.

Read the brief

Watch an agent hunt ransomware in a lake it can read.

Thirty minutes with our security and AI experts: a live hunt with Claude on Realm-optimized data in Databricks, starting from nothing but a CISA advisory and a table name.

Book a Live Threat Hunt

Nothing to install, no data to share. Want it on your own logs? We run that next.