CIM Normalization Security Data Engineering AI-Powered Tooling Splunk® Certified

Your Splunk® data.
Normalized.
Validated.
Production-ready.

Independent security data engineering consulting specializing in CIM normalization at scale, with AI-accelerated tooling built to make slow, manual work fast and repeatable.

Raw machine data refined into validated, deployment-ready intelligence

CIM normalization is a bottleneck.
It doesn't have to be.

Most organizations lack any structured process for CIM normalization. The result: inconsistent coverage, hidden field gaps, ES capabilities that underperform, and correlation searches built on brittle technology-specific filters instead of data models.

Without MDI

The Ad-Hoc Reality

  • 8-12 hours per sourcetype, manually
  • No standardized process or validation methodology
  • Field gaps discovered in production
  • Acceleration health untested
  • No audit trail or compliance reporting
  • New sourcetypes excluded from ES correlation searches
  • Correlation searches locked to index/sourcetype filters instead of data models
With MDI

AI-Automated Normalization

  • AI-accelerated normalization, automated. Full engagement includes scoping, phased delivery, and validation.
  • Prescribed value validation: fields checked for correct values, not just presence
  • Coverage gaps identified before and after normalization
  • Acceleration health monitored continuously
  • Full TA documentation auto-generated
  • Custom data model support included
  • AI-assisted migration from filter-based to data model-driven correlation searches

Purpose-built tools.
Practitioner-delivered results.

Turning Data Into Gold

Every tool I've built solves a real problem I encountered in enterprise security environments. No consulting theater. Just working solutions that extract real value from your machine data.

Core Tools

CIM Assessment Toolkit (CAT)

Splunkbase app for CIM health assessment. Validates field coverage, acceleration status, and custom data model compliance. Version 2.0 includes prescribed value validation and gap analysis panels.

Splunkbase App More info

Paydirt

Free, open-source tool that scrubs CUI, PII, PHI, and credentials from Splunk log exports. Runs entirely on your own machine as a self-contained browser tool or Python CLI, with no installation and no network calls. CMMC, HIPAA, and GDPR aware.

Free & Open Source More info

Data Refinery

Refines raw machine data into validated, CIM-compliant Splunk Technical Add-ons and Cribl packs: packaged, documented, and ready to deploy. Read-only exports go in; deployment-ready artifacts come out.

Normalization Pipeline More info

Supporting Services

ES Field Optimization & Cribl Cost Reduction

Systematic analysis of Enterprise Security field usage to eliminate unnecessary data ingestion. Cribl-based pipeline optimization with documented ROI and measurable license cost reduction.

In Development More info

ES Correlation Search Modernization

AI-assisted migration from brittle index/sourcetype filter-based correlation searches to scalable, data model-driven searches. Improves ES coverage, reduces maintenance overhead, and unlocks the full value of CIM normalization investments.

In Development More info

Performance & Capacity Analytics (PCA)

Splunk-native server performance measurement, resource utilization trending, and capacity planning. Clear visibility into how a deployment is holding up as data volumes climb.

Supporting More info

Data Source Integrity Monitor (DSIM)

Monitors Splunk data flows for volume anomalies, tracking events, hosts, and sources at 15-minute intervals and alerting when values deviate from established statistical baselines.

ML Tool More info

DataGen

Generates synthetic data flows for ingestion into Splunk or Cribl. Provides realistic, repeatable test data for validating apps, TAs, dashboards, and threat detections without touching live production feeds.

Testing Tool More info
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More to come

AI isn't a buzzword here.
It's how the work gets done.

Every engagement benefits from AI-powered tooling built and continually refined to solve specific, hard problems in security data engineering.

  • Automated field mapping inference across complex sourcetypes
  • AI-driven CIM normalization automation, with full coverage records and validation status reporting
  • ML anomaly detection for pipeline health and data drift
  • Continuous improvement loop: tools get smarter with every engagement iteration
  • Practitioner judgment combined with AI throughput. Not one or the other.

Independent practitioner.
Deep specialist.

I'm James H. Baxter, founder of Machine Data Insights, a security data engineering specialist with decades of experience building analytical tools and automation solutions for problems I've identified firsthand across enterprise environments.

I don't run a bench of consultants or sell you a methodology framework. I work directly on your environment, apply tools I've built and refined, and deliver measurable outcomes. My clients get my full attention, not a project manager and a junior analyst.

My focus is narrow by design: CIM normalization, security data integrity, and the AI-powered automation tooling that makes both dramatically faster and more reliable. That focus is what makes AI-accelerated delivery possible.

"There's Gold in that Data!"®

Let's talk about your data.

If you're dealing with CIM coverage gaps, slow normalization cycles, or ES data quality issues, I'd like to hear about it.

Email
Location Winter Springs, FL · Remote-first
Hours Mon-Thu, 9am-5pm ET