AI ADVISORY SERVICES · DIAGNOSTIC ENGAGEMENT
Assess Your AI Data Readiness
Contextual Data Readiness Assessment (CDRA) — a diagnostic for AI-ready security data.
CDRA is the first step in building an AI-ready data environment. We connect and measure your existing data, identify where context and temporal knowledge are missing, demonstrate how those gaps affect AI outcomes, and establish a foundation you can continue building on with Knowledge Grid.
A structured, vendor-neutral assessment of your temporal data
The CDRA determines whether an organization's security — or other temporal — data is organized, structured, and contextualized well enough to support advanced analytics, anomaly detection, temporal reasoning, and AI-driven workflows.
Rather than simply asking “Do you have the data?”, the CDRA evaluates whether that data contains the structure, relationships, temporal awareness, and context required for machines to reason effectively over it.
“It's not just about the data you have — it's what you can do with it.”
Comprehensive analysis
Across all five CDRA domains, scored on evidence rather than opinion.
Real-world simulation
Analytics and AI outcomes run against your actual data, not a reference set.
Prioritized roadmap
Actionable insights sequenced into near-term, mid-term, and strategic work.
Evaluating the readiness of your temporal data
The CDRA evaluates temporal data across five essential domains to determine how well it can be understood, connected, analyzed over time, and used to drive outcomes.
Data Coverage & Fidelity
Determines whether the right temporal data is captured completely, accurately, and consistently.
FUNCTION
- Source breadth and depth
- Data completeness
- Accuracy and consistency
- Time synchronization
- Gaps, duplicates, and noise
Data Structure & Usability
Evaluates how well the data is organized, modeled, and prepared for efficient use and analysis.
FUNCTION
- Data models and schemas
- Standardization and formats
- Metadata and documentation
- Data accessibility
- Reusability and quality scores
Context & Relationship Modeling
Assesses the ability to connect data into meaningful entities, relationships, and business context.
FUNCTION
- Entities and key attributes
- Relationship capture
- Business context enrichment
- Lineage and provenance
- Semantic consistency
Temporal & Behavioral Awareness
Evaluates how well the data captures, aligns, and expresses time-based events, sequences, and behaviors.
FUNCTION
- Event time accuracy
- Time granularity and windows
- Sequences and patterns
- Behavioral baselines
- Change and state tracking
Analytics & AI Reasoning Readiness
Determines how ready the data is to power analytics, machine learning, and AI-driven decision making.
FUNCTION
- Feature readiness
- Analytical and AI use cases
- Data quality for ML/AI
- Signal-to-noise ratio
- Outcome potential
HOW THE FIVE DOMAINS WORK TOGETHER
These domains are interdependent. Strong performance in one amplifies the others — together they determine how effectively your temporal data can be understood, predicted, and used to drive meaningful outcomes.
The Contextual Data Readiness Index (CDRI™)
A single 0–100 score for overall readiness across all five domains, supported by domain-level findings, outcome-quality testing, gap analysis, and a prioritized roadmap.
FIVE EVALUATION DOMAINS (LOCKED WEIGHTS)
Data & Structure
Context & Correlation
Temporal & Behavioral
Analytics & AI Readiness
Governance & Trust
CDRI™ SCORE
0 – 100
Overall readiness across all five domains
SCORING SCALE (PER DOMAIN)
What you receive
The CDRA engagement produces a comprehensive set of deliverables designed to translate assessment findings into clear, actionable business and technical outcomes.
Executive Summary
Overall CDRI™ score, maturity level, key findings, business impact, risks, and opportunities.
Contextual Data Maturity Report
Domain-by-domain evidence and findings in detail.
CDRI™ Scorecard
Performance across all five evaluation domains.
Outcome Quality Analysis
Task-battery results, output quality, and the readiness–outcome delta.
Structured Gap Analysis
Structural, contextual, temporal, and analytical deficiencies identified.
Prioritized Roadmap
Recommended improvements sequenced across near-term, mid-term, and strategic horizons.
Service Engagement Overview
01. EVALUATE & DISCOVER
We begin with dedicated discovery sessions to map your data landscape, perform a fit assessment, and identify high-value security use cases tailored to your environment.
02. DEPLOY & INTEGRATE
Seamless integration of the Knowledge Grid Platform with your existing security stack and data sources, establishing a unified cognitive data layer without operational friction.
03. OPERATE & OPTIMIZE
Continuous model tuning and anomaly review in close collaboration with SOC and MSSP teams to ensure optimal signal-to-noise ratios and proactive threat response.
Objective. Structured. Outcome-focused.
Transform data into context, context into insight, and insight into impact. Start with a clear, evidence-based understanding of your data readiness and the path forward.
Request a CDRA