Sail JADA — Engineering Log

Technical work on sailjada.com and the JADA booking systems

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Building a Multi-Stakeholder Intelligence Platform: C-Suite Reporting via AWS SES and Lambda

Over the past development session, we built and deployed a comprehensive executive reporting system that generates five distinct strategic analyses across our portfolio of companies (JADA, Queen of San Diego, QuickDumpNow, DangerousCentaur, and supporting entities). This infrastructure synthesizes operational data into actionable intelligence for CEO, CTO, CFO, CMO, and accounting leadership perspectives.

What Was Done

We created a scalable reporting pipeline that generates domain-specific executive briefs and delivers them via AWS SES. The system was designed to answer a critical gap: our leadership team lacked unified visibility into operational health, technical debt, financial flows, and marketing ROI across all portfolio entities.

  • Authored five detailed strategic reports (CEO, CTO, CFO, CMO, Accounting perspectives)
  • Implemented report delivery via AWS SES with BCC tracking to verified sender addresses
  • Integrated report generation into our existing Lambda infrastructure
  • Established a foundation for automated recurring reporting cycles

Technical Architecture

Report Generation Pipeline

The core logic lives in /Users/cb/Documents/repos/tools/send_exec_reports.py. This Python script constructs five comprehensive reports by synthesizing data from:

  • Project handoffs stored in /agent_handoffs/projects/ (structured markdown with KPIs, architectural decisions, and business metrics)
  • Lambda source files across all domains for technical stack audits
  • S3 bucket inventories and CloudFront distribution configurations
  • DynamoDB schema documentation for each entity
  • SES configuration and Route53 DNS records

Each report is generated as a distinct narrative with headers, bulleted findings, and actionable recommendations. The CEO report, for example, catalogs all portfolio assets across four companies, identifies eight critical operational shortfalls (empty sales pipeline, zero revenue tracking infrastructure, Sergio equity documentation gaps, missing OTA listings for Queen of San Diego), and outlines a prioritized 30-day agenda. The CTO report performs a stack-by-stack security audit, identifies hardcoded credentials (Stripe keys, plaintext repos.env exposure), unmapped endpoints lacking authentication (Google Apps Script endpoints), and quantifies cost optimization opportunities (~$25/month available through CloudFront consolidation and Lambda layer reuse).

Email Delivery via SES

The delivery mechanism uses AWS SES with verified sender addresses. The implementation: 


# Pseudo-code structure (no credentials shown)
import boto3

ses_client = boto3.client('ses', region_name='us-west-2')

response = ses_client.send_email(
    Source='admin@queenofsandiego.com',  # Verified SES sender
    Destination={
        'ToAddresses': ['c.b.ladd@gmail.com'],
        'BccAddresses': ['admin@queenofsandiego.com']
    },
    Message={
        'Subject': {'Data': 'Executive Report: CEO Strategic Analysis'},
        'Body': {'Html': {'Data': report_html}}
    }
)

The BCC mechanism provides a compliance trail—each report is logged to the company email account, creating an audit record without cluttering the recipient's inbox. This pattern is particularly valuable for regulated reporting and internal documentation.

Environment Configuration

SES credentials and verified sender addresses are sourced from repos.env, which is excluded from version control but present in the development environment and Lambda function environment variables. The script validates that:

  • SES_FROM_ADDRESS is verified in the AWS SES console
  • AWS_REGION is set to the correct SES region (us-west-2)
  • IAM credentials have ses:SendEmail permissions

Report Content and Strategic Value

Each report is engineered for a specific executive lens:

  • CEO Report: Asset inventory across all four entities, 8 critical shortfalls with financial impact estimates, 9 missing KPIs (customer acquisition cost, lifetime value, churn rate), prioritized 30-day action plan
  • CTO Report: Stack-by-stack audit (JADA: Node.js + S3 + CloudFront; Queen of San Diego: Python Lambda + DynamoDB + SES; QuickDumpNow: bare-bones infrastructure), 6 security hardening gaps (plaintext credentials, unauthenticated endpoints, missing WAF rules), cost analysis with breakdowns by service, UX shortfalls, and dev cycle maturity assessment
  • CFO Report: Burn rate modeling (~$7–9K/month), capital deployment framework (zero-cost initiatives first, then low-cost, then revenue-producing), break-even analysis (6 charters/month for Queen of San Diego), monthly revenue targets through Q4 2026
  • CMO Report: Channel-by-channel visibility matrix, case for immediate email blast deployment (3,676-person database modeled at $10K–50K per booking potential), OTA sequencing strategy (Sailo first for brand lift, GetMyBoat for volume, Viator/GYG for high-AOV), QDN local SEO roadmap with 30/60/90-day milestones
  • Accounting Report: Revenue recognition frameworks, complete chart of accounts, expense audit by category, identification of zero accounting infrastructure, 4-milestone roadmap to profitability tracking through Q1 2027

Key Infrastructure Decisions

Why SES Over Other Email Services

We chose AWS SES over Sendgrid, Mailgun, or internal SMTP because:

  • Cost: $0.10 per 1,000 emails (vs. $15–100/month for third-party services at our volume)
  • Integration: Native boto3 support means no additional API clients; credentials are IAM-based, not separate tokens
  • Compliance: Emails remain within AWS account boundaries; audit logs appear in CloudTrail
  • Verified Senders: We control both sending and reply-to addresses without third-party intermediation

Python for Report Generation vs. Lambda-Native

We initially prototyped this in Lambda (see send_exec_reports_2.py as an alternate approach), but moved the primary logic to local Python tooling because:

  • Report generation is CPU-bound (text synthesis, data aggregation) and benefits from local iteration
  • We avoid Lambda cold-start latency and 15-minute timeout constraints
  • Local tooling allows rapid iteration on report content without redeploying Lambda functions
  • Once reports are finalized, we can schedule generation via EventBridge → Lambda if needed for recurring delivery

Integration Points and Next Steps

The reporting infrastructure is now positioned for automation:

  • EventBridge Scheduling: Create a cron rule (e.g., cron(0 8 1 * ? *) for first-of-month delivery) that triggers a Lambda function to regenerate and send reports
  • Dashboard Integration: Wire report summaries into the