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Daily build note · June 25, 2026

Freight AI Pilot Control Tower

A packaging layer that reads the existing Freight Exception Triage Studio output and generates AI Product Manager pilot artifacts: opportunity map, workflow discovery map, prioritization...

AI Product Management For Logistics, Freight Brokerage, Carrier/Shipper Operations, Dispatch, Pricing, Tracking, Exception Management, And Transportation Workflow Automation Build note published Public demo coming soon

What shipped

Built a local Python CLI package named freight_ai_pilot_control_tower with three commands:

  • sample-pack --path <workspace> creates a synthetic Freight Exception Triage Studio-compatible triage/triage-pack.json.
  • generate-control-tower --path <workspace> converts that triage pack into pilot-control Markdown, CSV, and JSON artifacts.
  • validate-control-tower --path <workspace> validates source contract, generated artifacts, KPI completeness, approval gates, synthetic-data boundaries, and unsafe automation markers.

The generated pilot-control/ pack includes opportunity mapping, workflow discovery, prioritization, KPI tree, evaluation scenarios, approval register, 30-60-90 rollout, PM narrative, and consolidated JSON export.

Architecture

  • Standard-library Python only: argparse, dataclasses, json, csv, pathlib, and collections utilities.
  • Deterministic generation: same source pack produces the same artifact pack.
  • Contract-first input: the new build reads the parent triage/triage-pack.json shape instead of copying the prior triage app.
  • Human-in-the-loop by default: sensitive freight actions remain approval-gated in source validation, generated artifacts, and verifier assertions.
  • Self-contained verification: verify.sh builds a demo workspace under /tmp without relying on the absolute parent build path.

Trimmed scope

  • No web UI.
  • No database.
  • No hosted deployment.
  • No real TMS, tracking, EDI, inbox, carrier, claims, payment, or workflow integrations.
  • No external AI/model/provider calls.
  • No autonomous execution of freight operations decisions.

Limitations

  • Ranking formulas are deterministic heuristics intended for pilot planning, not production optimization.
  • Source data is synthetic and compact; real use would require a sanitized export that matches the documented contract.
  • Validation checks structural safety and obvious unsafe claims, but it is not a legal, compliance, or freight safety review.
  • KPI baselines are demo assumptions derived from queue size and source fields.

Suggested next steps

  • Add a contract adapter for sanitized parent build exports if the parent pack evolves.
  • Add golden-file tests for artifact rendering when the source pack changes.
  • Add configurable owner/category mappings for a real discovery sprint.
  • Add a redacted-import checklist for sanitized TMS or tracking exports.
  • Add a human review worksheet that records weekly KPI readouts and approval-gate exceptions.