DRAIDIS Use Case
Offline-first decision support for repeatable airfield risk scoring and next-best-action guidance
The Challenge
Airfield risk is not a single checklist problem. Tower, radar, weather, maintenance, airfield management, and flight operations each hold partial context, while base-specific knowledge often lives with experienced airfield leaders. Without a repeatable assessment layer, risk decisions can depend on local habit, incomplete data, or who happens to be in the room.
How DRAIDIS Solves It
DRAIDIS applies the risk logic and source package your team selects to weather, tactical and operational data, and operator input. It calculates risk indicators, retrieves relevant guidance, proposes next actions, and records the decision trail. During the pilot, your airfield team tests source coverage, scoring logic, offline behavior, and record retention against real scenarios. Your team controls whether operating records may be used to evaluate or improve a model.
Package Authoritative Context
Load official e-pubs, AFIs, local base supplements, reviewed risk logic, user guidance, and reviewed local operating knowledge into a versioned local knowledge package.
Collect Operational Inputs
Tower, radar, weather, maintenance, airfield management, and flight operations submit structured inputs alongside weather, tactical, and operational context.
Validate Conditions
Guarded forms reject missing, out-of-range, stale, or conflicting entries before they can affect the risk assessment.
Assess Risk Layers
The rules engine evaluates regulatory gates, local constraints, weather factors, operational conditions, and tactical context to identify where risk layers are weakening.
Surface Relevant Guidance
Local RAG retrieves relevant publication, AFI, supplement, checklist, or user guide passages for likely violations or mandatory actions identified by the configured rules.
Recommend Next Best Action
The AI explanation layer presents the risk tier, source citations, confidence, unresolved assumptions, and recommended actions in plain language.
Align the Airfield Team
Share selected risk indicators, findings, and proposed actions between configured devices. Field tests cover connectivity, conflict handling, security, and offline behavior.
Record the Decision Trail
Retain the inputs, source versions, confidence, user actions, and approval history your team needs for review.
Solution Architecture
A plain-language view of how DRAIDIS connects airfield inputs, local guidance, risk logic, offline runtime, sync, and audit evidence without relying on public internet sources.
Inputs
Operational facts arrive from the sections and systems that own the context.
Knowledge Base
Authoritative guidance and local experience are packaged locally and versioned.
Assessment Engine
Rules and AI evaluate risk without making the recommendation opaque.
Operator Interface
The workflow is built to withstand improper input and repeated operational use.
Offline Runtime
The system works locally when internet access is unavailable or not authorized.
Sync and Audit
Recommendations remain traceable as devices reconnect or policy packages update.
Regulation Controls DRAIDIS Helps Enforce
The goal is not to replace commander judgment. It is to make mandatory checks explicit, cited, and repeatable so future risk decisions are less dependent on memory, local habit, or fragile manual logic.
Instrument Cross-Check Discipline
Required cross-check cues can be represented as explicit condition checks and mandatory callouts instead of relying on memory under pressure.
Low-Visibility Decision Gates
Weather thresholds, runway-specific conditions, wind updates, and approach constraints can trigger standardized recommendations before a team continues an operation.
Crew and Section Coordination
CRM-style handoffs become workflow states with named owners, required acknowledgements, and a record of who saw which recommendation.
Equipment and Safety Eligibility
Check inspection status, weight limits, gear configuration, and local safety controls before the team approves a risk recommendation.
Deployment Configuration
This reference design spans 2 DRAIDIS tiers. The pilot defines and tests the coverage needed for your environment.
DRAIDIS BRAVO
Runs the local risk application, guarded forms, selected source package, and workflow records. The pilot tests the chosen hardware, storage, and interfaces under constrained-network conditions.
DRAIDIS CHARLIE
Aggregates selected risk data, manages reviewed publication packages, and synchronizes chosen updates when connectivity permits.
Key Capabilities
Purpose-built AI capabilities for this mission set.
Regulation-Grounded Local RAG
Answers and recommendations cite the official publications, AFIs, local supplements, user guides, and local operating knowledge selected for the source package.
Risk Logic Hardening
Transforms fragile manual logic into versioned rules, input checks, and reviewed policy packages.
Multi-Section Risk View
Combines tower, radar, weather, maintenance, airfield management, flight operations, tactical data, and operational data into one shared assessment.
Violation Surfacing
Surfaces possible regulatory, procedural, or safety-control violations for operator review alongside the final recommendation.
Next-Best-Action Guidance
Recommends actions that reduce risk, clarify uncertainty, or trigger required escalation while preserving commander judgment.
Bad-Input-Tolerant Forms
Uses validation and review gates to flag changed logic, skipped fields, stale values, invalid ranges, and contradictory entries before an assessment is approved.
Local Processing
Keeps selected inference, retrieval, and decision records on the local node when public internet access is unavailable.
Mesh Sync and Evidence Export
Shares the selected risk posture across configured devices and exports decision records for review.
Performance Metrics
Local
Disconnected processing design
Multi
Section input workflow
Selected
Knowledge-source scope
Logged
Recommendation evidence trail
Plan a Pilot for This Workflow
Review how DRAIDIS could support airfield risk assessment, then define the interfaces, data, hardware, controls, and operating conditions your team wants to test.