ARIA: AI-Powered Resilience Intelligence & Analysis Platform

The Challenge

Resilience consulting and assessments in regulated industries are time-consuming, subjective and difficult to scale across large organisations.

$1.6B

Global business continuity management market by 2030, driven by pharmaceutical supply chain disruptions, regulatory mandates (ISO 22301, EU DORA), and critical infrastructure risks. Yet traditional consulting workflows remain manual, slow, and inconsistent.

Business continuity consultants in pharma and other regulated sectors need to triangulate multiple evidence streams—BCPs, employee surveys, stakeholder interviews—to produce validated maturity assessments for ISO 22301, BS 65000, and sector regulators. Manual synthesis requires significant time and tailored expertise per domain and is prone to bias. Critical industries need AI augmentation that maintains consultant expertise while delivering audit-grade traceability.

Evidence scattered across policies, survey data, and interview transcripts from multiple business units

Manual cross-referencing doesn't surface contradictions effectively (e.g., policy claims vs. operational reality)

Regulatory clients demand complete evidence traceability—every claim needs citations back to source documents

Traditional consulting timelines (8-12 weeks) don't match pharma's fast-moving risk landscape

The Solution

Multi-agent DAG orchestration. Evidence-by-design architecture. First pass consultant-grade findings for human-in-loop review in minutes versus days/weeks.

An AI-enabled automation workflow deploying 8 specialized AI agents coordinated through directed acyclic graph (DAG) workflows. Agents process documents, surveys, and interviews in parallel, then triangulate findings across all three evidence streams using the Design-Perception-Reality framework. Every maturity score links back to specific evidence with line-level citations.

Key Innovation: Hybrid intelligence model combines heuristic agents (fast, deterministic) with LLM synthesis (nuanced, context-aware) for optimal cost-efficiency and quality. Flexibility in integrate more complex agents and underlying AI models for increased performance if required.

Foundation Intelligence Layer

5 specialized evidence extraction agents

AGENT F1

Standards Intelligence

Maps regulatory requirements from ISO 22301, BS 65000, ISO/IEC 27001 to maturity domains. Provides clause-level citations with page numbers for audit traceability. Ensures assessments align with pharma compliance frameworks.

AGENT F2

Document Analysis

Extracts policy evidence from BCPs, frameworks, and procedures. Returns structured claims with exact section names and line ranges. Evidence-by-design preprocessing adds line annotations for precise source tracking.

AGENT F3

Survey Insight

Analyzes stakeholder perception data across organizational functions. Detects outliers and confidence gaps with respondent-level citations (ID, business area, role). Quantifies perception vs. documented reality.

AGENT F4

Interview Theme

Processes qualitative interview transcripts to extract operational reality. Preserves conversational context with turn-level citations (participant, turn number, date). Surfaces what actually happens vs. what policies claim.

AGENT F5 • LLM

Synthesis & Triangulation

Cross-validates findings using Claude Sonnet 4.5 with the Design-Perception-Reality framework: What policies document (F2), what stakeholders believe (F3), what operations reveal (F4). Automatically detects contradictions with confidence scoring.

AGENT F6 • ORCHESTRATOR

Current State Orchestrator

Coordinates F1-F5 through DAG workflow (Standards → [Documents + Surveys + Interviews] parallel → Triangulation). Generates complete maturity findings with BS 65000 scores, narratives, recommendations. For typical organisational node engagement, reduces analysis from 40+ hours to <2 minutes per domain.

Phase Orchestration Layer

From findings to implementation roadmap

AGENT P2 • HYBRID

Gap Analysis & Action Generation

Combines heuristic gap calculation (target - current maturity) with LLM-generated implementation actions. Prioritizes initiatives across Quick Wins, Critical Path, Schedule, Consider quadrants with 3-5 step guidance.

AGENT P3 • HEURISTIC

Roadmap Generation

Transforms gaps into quarterly implementation roadmap (Q1-Q4). Uses keyword-based dependency detection and rule-based sequencing. Automates strategic planning deliverable creation in <1 minute.

Example Assessment

Global Pharma Corp – ISO 22301 Readiness Assessment

Evidence Processed

25 policy documents analyzed
68 survey responses across 5 business functions
12 stakeholder interviews (operations, quality, regulatory)

Maturity Domains

Governance • Risk Management • Business Continuity Planning • Operational Resilience • Culture & Awareness

Results

Complete maturity assessment: <10 minutes (vs. 40+ hours manual)
47 evidence-backed findings with line-level citations
23 prioritized gaps across 5 domains
12-month implementation roadmap with dependency chains

System Walkthrough

From evidence collection to validated findings.

Consultant Dashboard

Central hub showing project setup, multi-agent status, and evidence collection progress. Track which AI agents are active, idle, or processing across documents, surveys, and interviews.

Document Intelligence Agent

Deep analysis of business continuity plans and frameworks. Extract key sections, identify gaps against standards (ISO 22301, BS 65000, BCI GPG), and map to resilience domains with line-level citations.

Survey Insights Agent

Function-by-function breakdown of survey confidence scores. Detect outliers, analyze question-level patterns, and surface perception gaps across organizational units with respondent metadata.

Interview Analysis Agent

Extract quotes from stakeholder interviews and cross-reference with documents and surveys. Link contradicting or confirming evidence across all three streams to validate operational reality.

Triangulation Dashboard

Unified view of validated findings with confidence scores. Review AI-generated insights marked as "Draft," add consultant notes, and approve findings before client delivery. Design-Perception-Reality framework in action.

Assessment Findings

AI-generated and manual findings with consultant validation workflow. Track draft, reviewed, and approved status. Add maturity scores and link to governance domains with complete evidence traceability.

Gap Analysis

Compare current state to target maturity levels across resilience domains. View gaps by domain with effort and impact indicators, recommended actions to close gaps, and alignment to ISO 22301 clauses.

Implementation Roadmap

Timeline for closing gaps and achieving target maturity. View initiatives by quarter with quick wins and critical path items. Automated dependency detection and sequencing across Q1-Q4.

Deliverable Generation

Export to Word (executive reports), PowerPoint (board decks), or interactive dashboards. Select findings to include, customize templates, and generate client-ready deliverables with evidence citations.

Client Portal

Client-facing AI assistant interface for exploring assessment results. Ask questions about survey responses, recommendations, and evidence. Upload new documents for real-time analysis.

Agent Configuration

Select and configure agents required for augmented assessment workflows. DAG orchestration management console showing agent dependencies and execution status.

Key Learnings

What we learned building ARIA

Multi-agent orchestration delivers consultant-grade speed

DAG coordination of 8 specialized agents transforms months of manual analysis into minutes of intelligent synthesis. Foundation agents (F1-F4) extract evidence in parallel; synthesis agent (F5) triangulates findings with complete source traceability.

Design-Perception-Reality framework catches what humans miss

Automated triangulation across policies, surveys, and interviews surfaces contradictions instantly. Example: Policy documents claiming annual exercises vs. interviews revealing 18-month gaps. This framework is critical for pharma compliance validation.

Evidence-by-design architecture is non-negotiable for regulated industries

Building citation traceability into preprocessing—not retrofitting—creates the audit trail pharma and financial services regulators demand. Every finding links to specific evidence with line-level precision.

Hybrid intelligence optimizes cost and quality

Heuristic agents (F1-F4, P3) provide fast, deterministic processing. LLMs (F5, P2) handle nuanced synthesis and creative action generation. Result: 9 LLM calls per analysis vs. 40+ if fully LLM-based.