Capabilities
How Logicon addresses the Decision Superiority for NATO Warfighters challenge
This page maps Logicon's technical capabilities to the NATO DIANA Decision Superiority Exemplar Effects it addresses: four strongly (#3, #5, #6, #10), three partially (#1, #4, #9), and clarifies which three effects (#2, #7, #8) are out of scope and handled by complementary modules within MSS NATO.
The NATO DIANA Decision Superiority challenge defines 10 Exemplar Effects that dual-use deep tech solutions should deliver to warfighters. Logicon directly addresses 4 of 10 Exemplar Effects strongly (#3, #5, #6, #10), with partial coverage of effects #1, #4, and #9. The remaining 3 effects (#2, #7, #8) are out of Logicon's scope and handled by complementary modules within MSS NATO.
Directly Addressed Effects
#1
Red/Blue Force Simulation (Partial)
Challenge Requirement
Red/blue/neutral simulation in wargaming environments.
/scenarios/baltic provides an adversarial scenario walkthrough with cumulative perturbation analysis stage-by-stage (UAV detection → cable severance → vessel manoeuvre → border buildup → hostile intent confirmation). Each stage triggers live engine inference and shows source activation, semantic drivers, and updated probability + confidence interval. Full agent-based wargaming with autonomous red/blue forces is handled by complementary MSS NATO modules.
#3
Probabilistic Modelling & Simulation
Challenge Requirement
Enable reinforcement learning, probabilistic modelling, and optimisation techniques to explore complex operational dynamics and improve decision support through repeated simulation and analysis.
Multi-model ensemble (logistic regression + decision stump forest, 60/40 weights) produces probability estimates measured at Brier 0.106 / AUC 0.95 on 480 resolved predictions. Gradient-boosted trees scaffolded for Phase 1 ensemble integration. Isotonic calibration (Pool Adjacent Violators) implemented and validated offline (20% Brier reduction backtested); production activation pending data diversity expansion across regions. Walk-forward temporal validation harness in place. Confidence intervals via ensemble variance.
#4
Course of Action Systemic Parameter Exploration (Partial)
Challenge Requirement
Course of action analysis through systemic exploration of operational parameters.
/scenarios/explorer enables operator-driven parameter variation across 16 sliders × 10 regions = 160 base what-if combinations. Each slider movement triggers live engine inference (debounced); probability, confidence interval, top-5 drivers with polarity, and delta-from-baseline update in real time. Logicon focuses on probabilistic impact assessment per parameter set; full COA framework features (side-by-side scenario comparison, scenario library, sensitivity analysis, batch comparison) handled by complementary MSS NATO COA tools.
#5
Automated Scenario Preparation
Challenge Requirement
Automate elements of scenario preparation and operational context development, such as initial conditions, dynamic stimulus material such as trigger events and media reporting on external events.
Auto-generates regional intelligence briefings from live OSINT: current operational environment (compiled from UCDP GED conflict events + GDELT media intelligence, cross-validated against ACLED), top drivers from 18-feature vector across 4 dimensions (conflict dynamics, information environment, financial stress, structural vulnerability), 30/90-day trends, and probabilistic base/upside/downside scenarios. Detects grey-zone activities and pattern-of-life deviations. Output available as structured JSON for COP integration or natural language for human consumption.
#6
Operational Planning & Assessment Support
Challenge Requirement
Support elements of the operational planning and assessment cycle, including decision support, order development, operations assessment, forecasting, and lessons learned.
Calibrated probabilistic forecasts across multiple echelons and time horizons (tactical: 7–30 days, strategic: 30–180 days, structural: 6–12 months) feed directly into the operational planning process. Supports Intelligence Preparation of the Battlespace (IPB), Course of Action (COA) development, and operations assessment. Complete audit trail (input snapshot → feature vector → model version → prediction → outcome) enables systematic lessons learned and doctrine refinement. Self-learning pipeline ensures continuous improvement.
#9
Natural Language Interface
Challenge Requirement
Enable intuitive interaction with the digital environment, including natural language interfaces alongside other analytical modalities such as forecasting, optimisation, and perception capabilities.
Natural language query system allows operators to ask questions in plain English: “What is the escalation probability for NATO’s Eastern Flank?” Responses include probability estimates, key drivers, confidence levels, and source attribution. Accessible via web interface or API endpoint.
#10
Open-Source & Commercial Data Integration
Challenge Requirement
Use commercial and open-source data sources, including structured defence datasets, targeting-relevant information, maritime and infrastructure data, and publicly available information, to strengthen situational understanding and analytical outputs.
Six active OSINT connectors in production feature vector: UCDP (primary conflict data — 347K geo-coded events since 1946), GDELT (15-minute media events), FRED (800,000+ macro-economic time series), OpenSanctions (60+ regulatory authorities), V-Dem (governance quality indices), World Bank (development indicators). WGI ingested for Phase 1 wiring; Conflict Forecast API integrated as external reference; ACLED used for cross-validation only (no production code, full Content Usage Terms compliance). All unified into standardised 18-feature vectors across 4 dimensions (conflict dynamics, information environment, financial stress, structural vulnerability) — strengthening situational awareness and enriching the Common Operating Picture (COP) across multi-domain operations.
Complementary & Out-of-Scope Effects
These effects fall outside Logicon's core domain but represent integration opportunities where Logicon outputs can augment partner platforms.
#2
Agent-Based Modelling
Agent-based AI representations of red, blue, neutral, and grey forces with autonomous decision-making. Out of scope — Logicon outputs probability estimates and driver attribution that can feed into agent-based simulation environments, but the agent modelling itself is handled by complementary MSS NATO modules.
#7
Targeting Workflows
Not addressed — Logicon focuses on operational and strategic echelon forecasting, not tactical targeting workflows.
#8
ISR Feed Processing (CV, Radar, FMV)
Not addressed — Logicon processes structured OSINT, not raw Intelligence, Surveillance and Reconnaissance (ISR) sensor data. ISR feeds can complement Logicon’s multi-source intelligence fusion.