Pilot-ready intelligence for resilient decisions.
QuantisNexis™ helps leaders see where institutional resilience is strong, where it is fragile, and what to do next—using the QNX v4.2 engine, Quantis Index™, QuantisSentra™ risk signals, and Quantis Advisors™ action logic.
A unified engine, not a black-box AI tool.
QNX Core™ provides the mathematical foundation, while advanced layers—RADAR, synergy, copula dependency, EFQM/Baldrige benchmarking, ML readiness, QuantisSentra, Quantis Advisors, and Quantis Narrator—add transparent diagnostic intelligence around the core result.
View technical foundation retained for methodology users
QNX Core™ is represented as a 25-variable engine integrating BMS, ATCG, VUCA, WOWA/Orness weighting, and the master equation. The platform also includes RADAR scoring, EFQM/Baldrige anchoring, Diamond-style ESI synergy, copula dependency diagnostics, ML readiness, outcome-label workflow, and Tito-Conti advisor logic.
QNX Core™
The deterministic scoring engine. Produces the Quantis Index from normalized organizational variables and pillar logic.
QuantisSentra™
Risk and decay signal layer using critical thresholds, synergy bottlenecks, anomaly flags, and trend conditions.
Quantis Advisors™
Tito-Conti-based diagnosis, treatment, and review logic with sector-specific ideal profiles.
Quantis Narrator™
Score-safe explanation layer. It explains QNX outputs but does not invent or alter scores.
QNX v4.2 system architecture.
The public website now reflects the current production direction: QNX v4.2 is pilot-ready, non-destructive, and designed to support dashboard, API, report, and future supervised ML workflows.
Start from your operating context.
QNX can present the same core engine through sector-specific language, ideal profiles, benchmarks, and advisory logic.
One engine. Multiple sector contexts.
Each module uses the same QNX Core foundation but adapts ideal profiles, thresholds, benchmarks, and advisory language for the sector context.
Climate™
Water, infrastructure, resilience, environmental agencies.
Government™
Cities, counties, state agencies, public governance.
University™
Higher education, research centers, institutional quality.
Health™
Health systems, service reliability, governance, safety.
Enterprise™
Organizations, non-profits, consulting and performance teams.
QNX v4.2 applied to NYC urban flood governance.
This clean demo case translates the ASCE NYC organizational genomics package into QNX outputs: Quantis Index, QuantisSentra flag, synergy bottleneck, copula tail-risk signal, Tito-Conti priorities, and client-ready report narrative.
NYC Urban Flood Governance Under Compound Flood Hazards
Based on the ASCE NYC submission package and the quantitative organizational genomics framework. Authorship corrected as: Morteza Shakeri Majd, Ph.D.; Dr. Mehrdad Rastgou.
QNX pillar profile
NYC shows strong analytics and governance capacity, while infrastructure resilience/process stability is the main bottleneck under compound flood stress.
Client narrative: NYC demonstrates moderate resilience under high compound hazard stress. Strong planning and governance partially offset exposure, but resilience/process stability remains the key improvement target.
Tito-Conti priority areas
| Rank | Pillar | Actual | Target | Status | Priority |
|---|---|---|---|---|---|
| 1 | RE | 0.54 | 0.82 | WARNING | 0.58 |
| 2 | ET | 0.76 | 0.88 | STABLE | 0.12 |
| 3 | EI | 0.77 | 0.82 | STABLE | 0.05 |
| 4 | AD | 0.79 | 0.80 | STABLE | 0.01 |
| 5 | IN | 0.81 | 0.80 | STRONG | 0.00 |
Top priority: RE — strengthen flood-critical continuity pathways, cross-agency resilience drills, and capital-program triggers.
Scenario results and copula tail-risk signal
The demo uses scenario outputs from the NYC package to create a simple joint low-tail risk proxy. The resulting copula-style diagnostic flag is elevated_cohort_tail_probability.
Executive-ready intelligence. Audit-ready evidence.
QNX produces structured outputs for leadership, technical teams, and pilot partners. The same engine can support dashboard views, reports, JSON/API responses, and Narrator summaries.
Ready for controlled pilots, demos, and partner feedback.
QNX v4.2 is ready for website synchronization, demonstration cases, API wrapper planning, and pilot data collection. Supervised ML becomes stronger as pilot outcome labels are collected.