Why standardized data matters for Splunk security and compliance

Security and compliance in Splunk depend on one foundational capability: consistent, standardized data. Yet data normalization — especially CIM mapping — remains one of the most manual, time‑consuming, and error‑prone tasks Splunk teams face.

In this demo, we show how Deslicer AI brings structure and confidence to data normalization, executing a complete, best‑practice‑driven workflow through a single conversation.

What happens behind the scenes

Rather than treating normalization as a one‑off task, Deslicer AI approaches it as a structured, auditable process.

In this demo, Deslicer agents execute a six‑step normalization plan:

• Verifying requirements and profiling existing data
• Auditing gaps in current field coverage
• Fetching Splunk data model documentation and best practices
• Generating field mappings, tags, and eventtypes
• Validating all additions against Splunk’s standardized data models
• Ensuring readiness for downstream use in ES and ITSI

Each step is executed and validated automatically — with full transparency.

From manual CIM mapping to standardized data — fast

The data normalization challenge

CIM mapping is critical, but costly. It often requires hours of manual effort, deep expertise, and repeated validation to ensure data is usable across security and observability use cases.

The Deslicer approach

Deslicer AI acts as an agentic intelligence layer for Splunk, combining data profiling, best practices, and validation into a single, coherent workflow. The result is normalized data that’s immediately usable — without manual back‑and‑forth.

The result in this demo

• 22,009 web events flowing into ES and ITSI
• 15 out of 15 CIM web fields mapped
• From 8 hours to 5 minutes to onboard a new data source

All completed in one conversation.

Why this matters

Standardized data isn’t just about cleanliness — it’s about trust.

By automating normalization with best practices built in, Deslicer AI helps teams:

• Reduce risk in security and compliance workflows
• Eliminate fragile, manual configurations
• Scale onboarding without scaling effort
• Build confidence in the data powering critical decisions

This is how teams move faster without compromising quality.

Who benefits most

This use case is particularly valuable for:

• Security and compliance teams using Splunk ES
• Platform teams onboarding new data sources at scale
• Organizations standardizing data across ITSI and observability
• Teams looking to reduce dependence on CIM experts