Proactive Risk Intelligence Engine

Turn early signals across eight regions into decisions an operations team can review.

Industry: Delivery marketplace
Business context: A fictional delivery marketplace managing fulfillment and customer support across eight regions.
Data sources: Synthetic operations combined with real public weather data. Risk scores and projections are calculated by the engine.

PRIE helps a fictional delivery marketplace spot emerging risk across eight regions and decide where Operations should investigate.

Beyond PRIE · Explore the ASIA vision

From signals to decisions

Every 15 minutes, n8n coordinates a Python pipeline that combines synthetic delivery operations with public weather signals. The dashboard shows regional risk, projected impact, and recommendations for human review.

From decisions to outcomes

Risk levels describe conditions before an incident. Incident severity describes observed impact after one begins. Open an incident to follow detection, the recommendation, and the simulated outcome. Prediction validation also reports false alarms and missed incidents.

Reading an early signal

In one demonstration window, Seattle showed a ticket-rate Z-score of +4.00 and a delivery pressure index of 51.1 out of 100. Read the two together before escalating: the ticket rate was unusual, while the delivery backlog was not showing sustained growth.

The dashboard documents rolling Z-scores, a conditional probability table inspired by Judea Pearl, and a queue energy indicator inspired by Lyapunov. The conditional probabilities are illustrative assumptions. Kolmogorov is cited for the foundations of probability.

Data and architecture

Weather comes from public sources. Orders and operational incidents are simulated. Risk scores and forecasts are derived from those inputs. Supabase stores the results, and Vercel serves the dashboard.

The broader visionConceptual architecture

Beyond PRIE. ASIA.

Adaptive Strategic Intelligence Architecture

PRIE implements selected principles from ASIA (Adaptive Strategic Intelligence Architecture), a conceptual enterprise-wide intelligence architecture designed to continuously connect external global signals with internal organizational conditions, evaluate operational resilience, and anticipate potential risks and opportunities across the entire value chain.

ASIA envisions a continuously evolving system capable of integrating geopolitical events, weather disruptions, cybersecurity threats, supply chain developments, market dynamics, competitor behavior, and internal performance indicators into interconnected models of organizational exposure and readiness.

Simulation & decision support

Through probabilistic modeling, dependency mapping, and continuously updated scenario simulations, ASIA would estimate cascading consequences, financial exposure, time-to-impact, and potential escalation pathways. It would also identify the conditions under which seemingly minor events could develop into significant organizational threats or opportunities.

The architecture would generate prioritized response scenarios, comparing projected outcomes against a no-action baseline while communicating uncertainty, assumptions, and decision deadlines. Organizational leadership would retain control over risk definitions, thresholds, and final decisions, supported by a dedicated Risk Intelligence Desk responsible for reviewing and escalating relevant findings.

Over time, the system would incorporate documented decisions, observed outcomes, and validated feedback to improve its predictive models and recommendations.

PRIE today · ASIA at enterprise scale

PRIE represents an early, deliberately limited implementation of this broader vision. Realizing ASIA at enterprise scale would require substantially greater data integration, validated mathematical models, computational infrastructure, cross-functional governance, and long-term organizational investment.

Future AGI Integration

Beyond its immediate applications, ASIA could serve as the foundational cognitive infrastructure for future Artificial General Intelligence (AGI) systems, providing the organizational memory, operational context, decision-making history, and strategic understanding necessary for an AGI to develop a comprehensive representation of an enterprise's unique identity, values, priorities, and institutional knowledge — effectively enabling it to understand and embody the organization's operational essence while remaining subject to human governance.