Multi-Stakeholder Executive Intelligence System: Building Real-Time Decision Support Across Four Maritime & Service Entities

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Over the past development cycle, we built and deployed a comprehensive executive reporting infrastructure designed to surface critical business intelligence across JADA, QueenofSandiego, QuickDumpNow, DangerousCentaur, and three ancillary properties. This system generates five simultaneous perspective reports — each tailored to a specific C-suite discipline — and distributes them via AWS SES to decision-makers in near real-time. Here's the technical architecture and reasoning behind this approach.

The Problem We Solved

The organization was operating without unified visibility into operational, financial, technical, and commercial health. Spreadsheets existed in silos. Handoff documentation lived in markdown files across multiple repos. No single view existed of what was broken, what was working, or what would move the needle on profitability. We needed a system that could:

Ingest data from five distinct business domains with different data models
Generate contextual analysis from five different professional perspectives simultaneously
Deliver those reports reliably via verified email channels
Be extensible to new domains and perspectives without architectural refactor

Architecture: The Multi-Perspective Report Engine

The core implementation lives in two Python files:

/Users/cb/Documents/repos/tools/send_exec_reports.py — Primary report orchestration
/Users/cb/Documents/repos/tools/send_exec_reports_2.py — Extended domain handling

The system operates on a persona-driven model: each report is generated by prompt-engineering a language model as if it were a specific type of executive reviewing the same raw data.

Execution Flow

1. Data Aggregation Phase

The script reads configuration from repos.env to locate:

AWS SES sender identity (verified address: admin@queenofsandiego.com)
Recipient email addresses (BCC'd for privacy)
Handoff documentation paths across the repos structure
Project inventory files listing all active entities

Data sources included:

/agent_handoffs/projects/ — All active project markdown files containing operational notes, blockers, and progress state
/sites/queenofsandiego.com/tools/ — Lambda function source code, frontend implementations, deployment history
Direct inspection of environment files and configuration to identify gaps (missing OTA integrations, Stripe key exposure, plaintext credential storage)

2. Persona-Based Report Generation

Five distinct reports were generated, each with a different evaluative framework:

CEO Perspective: Asset inventory, revenue leakage, organizational risk, 30-day prioritization
CTO Perspective: Tech stack audit, security hardening requirements, cost optimization, developer velocity improvements
CFO Perspective: Burn rate modeling, capital deployment framework, break-even analysis, monthly revenue targets
CMO Perspective: Channel-by-channel visibility, blast campaign ROI modeling, OTA sequencing strategy, 30/60/90-day milestones
Accounting Officer Perspective: Chart of accounts review, revenue recognition issues, expense categorization, profitability roadmap through Q1 2027

3. Email Delivery via AWS SES

Reports are sent using boto3 SES client with:

Verified sender: admin@queenofsandiego.com
Primary recipient: c.b.ladd@gmail.com
BCC recipients for governance and audit trail
HTML-formatted email bodies with proper MIME encoding

The SES configuration uses IAM permissions scoped to send-only on verified identities — no access to bounce/complaint handling or configuration management.

Three Additional Domain Reports

Beyond the five persona-based reports, we identified three additional business entities requiring distinct evaluation:

3028 51st St Rental Property: Real estate asset analysis, tenant quality, maintenance costs, revenue sufficiency
Expert Yacht Delivery: Standalone service delivery audit, client satisfaction metrics, operational efficiency, margin analysis
DangerousCentaur Client Portfolio: Billing gap audit, outstanding receivables, contract compliance, collection risk

These were queued for generation using send_exec_reports_2.py, which extends the persona framework to property management, service delivery operations, and accounts receivable perspectives.

Key Technical Decisions

Why Persona-Driven Prompting?

Rather than building separate business logic modules for each perspective, we leverage language model reasoning to apply disciplinary expertise. This has three advantages:

Extensibility: Adding a new persona (e.g., VP Sales, Head of Legal) requires only a prompt, not code changes
Consistency: All five reports analyze the same raw data, making cross-functional pattern-matching easier
Speed: We can add new evaluative frameworks in minutes, not sprint cycles

Why SES Instead of Transactional Email Services?

AWS SES is tightly integrated with our existing IAM and credential management. It's cost-efficient at this volume (5–8 reports/execution) and supports the BCC pattern we need for audit trails. The verified sender requirement ensures deliverability into corporate inboxes.

Why Environment Variables for Configuration?

All SES parameters, recipient lists, and data source paths live in repos.env. This decouples the script from hardcoded configuration and allows different execution contexts (local development, CI/CD, scheduled jobs) to point to different verified senders or recipient lists without code changes.

Execution & Validation

The reports were generated and sent in sequence:


# Pseudo-command (actual command runs with repo context)
python /Users/cb/Documents/repos/tools/send_exec_reports.py

# Output: 5 reports generated and sent
# CEO report: 9 missing KPIs, 8 critical shortfalls identified
# CTO report: 6 security gaps, 10 engineering actions prioritized
# CFO report: Burn rate $7–9K/month, break-even at 6 charters/month
# CMO report: 3,676-person blast campaign modeled at $10K–50K potential per concert booking
# Accounting report: 4-milestone profitability roadmap through Q1 2027

All emails were delivered within seconds. Verification included confirming BCC delivery and checking recipient inbox for proper formatting and tone consistency across personas.

What's Next

Scheduled Execution: Move report generation to EventBridge rule (weekly cadence recommended) to surface trends over time
Dashboard Integration: Create kanban cards on progress dashboard for each report finding, with assignment and tracking
Real-Time Data Hooks: Integrate DynamoDB streams to feed actual transaction data (