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Cybersecurity Data & AI Practice

Your security team has a data problem.
That's what we solve.

Data Products helps security-focused organizations build the data infrastructure, AI detection models, and governance frameworks that turn raw security telemetry into defensible outcomes — and regulatory compliance into competitive advantage.

Schedule a Discovery Call → Download: Security Data Readiness Assessment
80%
of security alerts go uninvestigated due to data overload and alert fatigue
3×
faster mean time to detect with ML-powered anomaly detection over rule-based SIEMs
$4.9M
average cost of a data breach for organizations without mature security analytics (IBM, 2024)

The Core Challenge

Security teams are drowning in data. Starving for insight.

Modern organizations generate billions of security events daily — from endpoints, networks, cloud workloads, identity systems, and third-party tools. The data exists. The problem is that most security organizations lack the data engineering, AI, and analytics infrastructure to make it actionable.

The result: alert fatigue, slow investigations, missed threats, and compliance reports built on spreadsheets.

"We have more data than ever. We have less clarity than ever. The gap in between is a data engineering problem — not a security tool problem."

— CISO, Fortune 500 Financial Services Firm
⚠️
Legacy SIEM Sprawl
Splunk, QRadar, and similar tools weren't designed for petabyte-scale telemetry. Query costs spiral. Data gets dropped. Retention shrinks.
🔍
No Single Source of Security Truth
Threat data lives in silos across EDR, NDR, cloud logs, and IAM systems. Analysts pivot between 7+ tools for a single investigation.
📋
Compliance Reporting Done Manually
NIST CSF, CMMC, SEC cyber disclosure, SOC 2 — each demands evidence that takes weeks to compile by hand, every audit cycle.
🤖
AI Promises, No Production Models
Security vendors sell "AI-powered" tools. Few organizations have the data infrastructure required to train and deploy models on their own telemetry.
⚖️
AI Governance Blind Spots
Security teams adopting AI for threat detection face new risks: model drift, bias, auditability gaps, and emerging regulatory exposure under NIST AI RMF and EU AI Act.

Data IQ™ for Cybersecurity

What we build for security-driven organizations

Every engagement applies Data Products' proven Data IQ™ framework to the specific data and AI challenges of security organizations — from strategy through full deployment.

Practice 01

Security Data Strategy & Cyber Risk Governance

We assess your current security data maturity, map gaps against NIST CSF, NIST AI RMF, CMMC, and SEC disclosure requirements, and build a multi-year roadmap with ROI validated at every milestone.

  • Security Data Maturity Assessment (scored against NIST CSF)
  • AI governance framework for security ML models
  • Cyber risk data inventory and classification
  • Compliance automation roadmap (SOC 2, CMMC, SEC)
  • Data council model for security data ownership
Entry Point Engagement · 4–6 Weeks

Practice 02

Security Data Platform Modernization

We architect and build modern security data lakes and lakehouse platforms on Azure Sentinel, Microsoft Fabric, Databricks, and Snowflake — replacing brittle, expensive SIEM infrastructure with scalable, governed data foundations.

  • SIEM-to-lakehouse migration architecture
  • Unified security telemetry pipeline (endpoint, network, cloud, identity)
  • Real-time streaming ingestion for threat data
  • Data retention, access control, and audit logging
  • Security data quality and observability framework
Core Engineering · 8–16 Weeks

Practice 03

AI Threat Detection & Anomaly Modeling

We design and deploy custom ML models trained on your organization's own security telemetry — delivering threat detection, user behavior analytics (UEBA), and insider risk models that outperform vendor black-box tools.

  • Anomaly detection models for network, identity, and endpoint data
  • UEBA: user and entity behavioral baselines
  • Insider risk scoring pipelines
  • GenAI-powered analyst copilots for SOC investigations
  • Model explainability and auditability documentation
AI & GenAI · 10–20 Weeks

Practice 04

Security Operations Analytics & Dashboards

We build Security Operations Center dashboards, executive risk reporting, and compliance evidence packages that give your team — and your board — real-time visibility into security posture, mean time to detect, and regulatory status.

  • SOC performance dashboards (MTTD, MTTR, alert volume, false positives)
  • Board-level cyber risk reporting (Power BI, Tableau)
  • Automated compliance evidence packages for auditors
  • Threat intelligence analytics and geospatial risk mapping
  • Analytics-as-a-service subscription model available
Analytics · 6–12 Weeks

Where we have deepest impact

Industries we serve

Cybersecurity data problems are universal. Our domain expertise is concentrated where the regulatory pressure and data complexity are highest.

🏦
Financial Services & Insurance
Fraud detection pipelines, SEC cyber disclosure compliance, risk analytics, and anti-money laundering ML models built for the industry's data governance requirements.
🏥
Healthcare & Life Sciences
HIPAA-compliant security data platforms, ransomware detection models, medical device telemetry analysis, and clinical network threat monitoring.
🏛️
Government & Public Sector
CMMC readiness, federal security data modernization, NIST RMF implementation, and threat intelligence analytics for defense-adjacent and civilian agencies.
🏭
Manufacturing & Critical Infrastructure
OT/IT convergence data platforms, IoT security telemetry integration, supply chain threat analytics, and ICS anomaly detection for operational environments.
⚖️
Professional Services & Legal
Client data protection platforms, insider threat modeling, privilege access analytics, and breach response data forensics infrastructure.
☁️
Technology & SaaS
Cloud-native security data lakes, multi-tenant threat isolation, SOC 2 Type II evidence automation, and developer security analytics (DevSecOps data pipelines).

How We Work

A proven path from security data chaos to operationalized intelligence

1

Weeks 1–2

Security Data Assessment

We audit your current data sources, tooling stack, governance posture, and maturity against NIST CSF and AI RMF. Deliverable: scored maturity report with prioritized gap analysis.

2

Weeks 3–6

Architecture & Roadmap

We design the target state: unified security data platform, AI/ML model plan, and compliance automation architecture. Deliverable: multi-year roadmap with investment-to-outcome mapping.

3

Weeks 6–16

Platform Build & AI Deployment

Our engineers build the lakehouse, ingest pipelines, and detection models — leveraging Microsoft, IBM, Databricks, and Snowflake partnerships for enterprise-grade delivery at speed.

4

Ongoing

Operate & Optimize

Analytics-as-a-service, model monitoring, compliance reporting, and continuous improvement. We embed alongside your team, not alongside your ticket queue.

Technology Partners

Start Here

Schedule your Security Data Readiness Assessment

A 45-minute discovery call with our team. We'll assess your current data and AI security posture, identify your highest-leverage opportunities, and outline a realistic path forward — with no obligation to proceed.

Book a Discovery Call → Download Assessment Framework

Improving Lives Through Data™ · Data Products LLC · Chicago, IL

Common Questions

What organizations typically ask

Are you a cybersecurity firm or a data firm? +
We are a data and AI consulting firm. We don't compete with your MSSP, your SOC vendor, or your endpoint tool — we build the data infrastructure that makes all of them perform better. Think of us as the team that ensures your security data is properly engineered, governed, and ready for AI.
Do you work with our existing security tools? +
Yes. We integrate with your existing stack — Splunk, Microsoft Sentinel, CrowdStrike, Palo Alto, Okta, and others. Our role is to build the unified data layer and analytics capability on top of your existing investments, not replace them.
How quickly can we see results? +
Our Security Data Assessment deliverable is typically complete within two weeks and provides immediate, actionable findings. For full platform builds, teams typically see measurable improvements in detection coverage and investigation speed within 90 days of deployment.
How does this intersect with NIST AI RMF and EU AI Act compliance? +
Any AI model used for security decisions — threat scoring, anomaly detection, identity risk — falls within emerging AI governance frameworks. We build explainability, auditability, and risk documentation into every AI model we deploy, ensuring your security AI posture is defensible under current and emerging regulatory requirements.
What size organizations do you typically work with? +
We primarily serve mid-market and enterprise organizations with 500+ employees, active compliance requirements, and dedicated security functions. We also work with government agencies and public sector entities. If you're investing in a security data initiative, we're likely the right size partner.