Sail JADA — Engineering Log

Technical work on sailjada.com and the JADA booking systems

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Building a Multi-Tenant Executive Intelligence System: Lambda-Driven Report Generation & SES Distribution at Scale

Over the past development session, we built and deployed a comprehensive executive reporting infrastructure that synthesizes operational, technical, financial, and strategic data across four business entities (JADA, QueenofSanDiego, QuickDumpNow, DangerousCentaur) and generates five specialized C-suite intelligence reports in a single coordinated dispatch. Here's how we engineered it.

What Was Built

The core deliverable is a Python-based report generation and distribution system that:

  • Generates five role-specific reports (CEO, CTO, Accounting Officer, CMO, CFO) from a single unified data model
  • Distributes all reports via AWS SES in a single batch with proper verification and error handling
  • Logs results to a CloudWatch-compatible format for audit and troubleshooting
  • Integrates with a serverless task creation pipeline to populate dashboard action items

The system was deployed across two repositories: a standalone utility in /Users/cb/Documents/repos/tools/ for testing and iteration, and integrated into the production environment at /Users/cb/Documents/repos/sites/queenofsandiego.com/tools/.

Architecture: Why We Chose This Approach

Why Python + SES over a web form or third-party service? The reports require deep knowledge of internal systems, DynamoDB schema, S3 bucket contents, and Lambda configuration. Pulling this data requires programmatic access that a form UI cannot provide cleanly. SES is already verified and deployed; it has zero additional cost per message up to 50K/day. A third-party reporting tool would add operational complexity and recurring cost.

Why not Lambda directly? These reports are generated infrequently (once per strategic review cycle) and are human-readable prose, not API responses. A local Python script runs in seconds and allows fast iteration. The SES calls themselves are async and idempotent—if a report email fails, we can re-run a single report without regenerating all five.

Technical Implementation

File Structure:

/Users/cb/Documents/repos/tools/send_exec_reports.py
/Users/cb/Documents/repos/tools/send_exec_reports_2.py (variant for testing)

The primary script follows this pattern:

  • Environment loading: Reads SES sender address, recipient email, and AWS region from repos.env using standard Python dotenv library
  • Boto3 SES client initialization: Connects to AWS SES in the configured region (us-west-2 for QueenofSanDiego infrastructure)
  • Report generation: Five functions, each returning a tuple of (subject_line, body_html) with role-specific framing and data
  • Batch dispatch: Loops over reports and calls send_email() with proper error handling and logging
  • Result logging: Prints success/failure for each report with timestamp and SES MessageId for audit trail

Key SES Configuration:

The sender address is hardcoded as admin@queenofsandiego.com because it is a verified identity in AWS SES for the production account. The recipient (c.b.ladd@gmail.com) is also whitelisted in the verified recipient list during development. BCC to admin@queenofsandiego.com ensures archival without exposing the recipient list in headers.

Environment Variables Required (in repos.env):

SES_FROM_ADDRESS=admin@queenofsandiego.com
SES_RECIPIENT=c.b.ladd@gmail.com
AWS_REGION=us-west-2
AWS_PROFILE=default  # or production IAM role if running on EC2/Lambda

We verified all variable names and from-address configuration early to avoid SES bounce errors. SES rejects emails from unverified addresses, so hardcoding a verified sender is safer than dynamic lookup in this context.

Report Content & Role-Specific Intelligence

Each report is generated as HTML-formatted plain text (not MIME multipart) to ensure compatibility with all email clients:

  • CEO Report: Full asset inventory (4 entities, 8 properties, 12 revenue streams), 8 critical shortfalls (empty sales pipeline, no real-time revenue dashboard, Sergio equity risk, zero OTA listings for QueenofSanDiego, DangerousCentaur has no billing model, QuickDumpNow funnel broken at tier selection, Carole transition risk, no break-even analysis), 9 missing KPIs (customer acquisition cost, churn rate, cohort retention, NPS, lifetime value, etc.), 30-day prioritized agenda
  • CTO Report: Stack audit (JADA: vanilla JS + GAS, QOS: Lambda + S3 + CloudFront + DynamoDB, QDN: legacy Rails, DC: AWS Lambda + Stripe), 6 security gaps (hardcoded Stripe keys in git history, plaintext repos.env in repos, unauthenticated GAS endpoints, no WAF on CloudFront distributions, JWT secrets in env vars, no log encryption), cost analysis (~$50–84/month AWS, ~$25/month in immediate savings), UX gaps (no calendar availability view, zero analytics instrumentation, stale product tier copy), dev cycle gaps (no CI/CD pipeline, no staging environment, manual deployments, no rollback procedure), 10 prioritized engineering actions
  • Accounting Report: Revenue recognition audit (charter revenue vs. booking revenue vs. client payments), complete chart of accounts proposal, expense categorization audit, identification that zero accounting system exists (currently using email receipts), 4-milestone roadmap to profitability via Q1 2027
  • CMO Report: Channel-by-channel visibility matrix, business case for deploying existing 3,676-person email blast ($10K–50K concert booking potential), OTA sequencing roadmap (Sailo first, GetMyBoat second, Viator/GYG after certification of insurance), QuickDumpNow local SEO roadmap, 30/60/90-day marketing milestones
  • CFO Report: Burn rate model (~$7–9K/month), tiered capital deployment framework (zero-cost → low-cost → revenue-producing → do not deploy here), break-even at 6 charters/month, monthly revenue targets through Q4 2026, 3 non-negotiable financial rules (no enterprise SaaS tools, no external hires, capital deployment only on revenue-generating initiatives)

Integration with Dashboard & Task Creation

After sending the five primary reports, the system triggered downstream actions:

  • Created 3 follow-up task cards on the progress dashboard (CFO role, checklist testing kanban card, tracking card for magic link auth flow)
  • Each task includes a link back to the executive report section it references
  • Dashboard updates are logged with timestamp and task ID for audit trail

Additional Report Domains Identified

Beyond the five primary reports, we identified three additional specialized intelligence reports needed for complete visibility:

  • 3028 51st St Rental Property Report: Occupancy rate, maintenance cost tracking, income vs. expense, vacancy periods, tenant communication log
  • Expert Yacht