Diagnostic Products
Know before
Know before
you deploy.
ChainLytix diagnostics measure the exact variables that predict whether a supply chain AI deployment will succeed or fail — validated across 202 real-world deployments with 85.6% accuracy.
Free · Instant Results
SCOR-DS Readiness Check
Free · 5 minutes
Instant domain-level scores
20-question assessment across all 5 SCOR domains
Domain scores: SOURCE, PLAN, MAKE, DELIVER, RETURN
Readiness level: High, Moderate, or Early
Top 3 prioritized recommendations
Weakest domain identified with specific gap
Paid · 48-Hour Delivery
SCOR-DS Diagnostic Report
$750 · per report
Full written report in 48 hours
Everything in the free check, plus full written analysis
Anti-pattern screening: Trust Deficit, Legacy IT, Regulatory, Privacy
Agent architecture recommendation (MAS vs. other types)
Use case prioritization ranked by readiness score
12-18 month readiness roadmap with sequenced actions
Benchmarked against 202-deployment research dataset
Enterprise · Custom Scope
Enterprise AI Readiness Program
From $12K · 4-8 weeks
Full program with stakeholder workshops
8-12 use case evaluation across all 15 SCOR-aligned tasks
Organizational anti-pattern assessment with all 5 variables
Executive investment roadmap with ROI estimates
Pilot design for highest-readiness use case
Governance framework and change management plan
90-day execution timeline with KPIs
What We Measure
The variables that actually
The variables that actually
predict outcomes.
Each ChainLytix diagnostic measures the same dimensions used in the 202-case logistic regression model that predicts deployment success with 85.6% accuracy.
📊 SCOR Domain Readiness
Scored across all 5 SCOR-DS domains — SOURCE, PLAN, MAKE, DELIVER, RETURN. Each domain maps to specific supply chain tasks where AI agents are being deployed today.
⚠️ Anti-Pattern Screening
Screens for the 4 statistically significant failure predictors: Trust Deficit (−98% odds), Legacy IT Debt (−96%), Regulatory Risk (−86%), and Privacy Risk (−78%). These alone explain the majority of deployment failures.
🔧 Agent Architecture Fit
Multi-Agent Systems succeed at 78.6% vs. 48.5% for other architectures (OR = 8.5, p = .029). The diagnostic recommends the right architecture type for your operational context.
🏗️ Process Physics Assessment
Evaluates the underlying traits and constraints of your supply chain tasks — decision frequency, data determinism, error tolerance, and 11 other dimensions from the TCM framework.
📈 Deployment Stage Analysis
Success rates improve from 59.1% at pilot stage to 77.8% at scaled production. The diagnostic tells you whether you're ready to advance or need to consolidate.
🎯 Use Case Prioritization
Across 15 SCOR-aligned tasks, readiness varies dramatically. The diagnostic ranks your specific use cases by probability of success — not vendor hype, not gut feel.
The Research Behind It
Built on evidence,
Built on evidence,
not opinions.
202
real supply chain AI deployments in the research dataset
85.6%
model classification accuracy (logistic regression)
15
SCOR-aligned tasks scored across 14 readiness dimensions
p<.001
significance level for 4 of 5 anti-pattern predictors
Start with the
free diagnostic.
20 questions. 5 SCOR domains. Instant readiness scores and recommendations — built on 202 real deployments.