Can AI replace Point.me?

Build a closest honest personal substitute for Point.me in an empty repository.
Use Next.js 15, TypeScript, SQLite, MapLibre GL, and user-supplied map and travel APIs; do not offer alternative stacks.
The core loop is: store manually researched award options, compare user-entered points values, map places and reservations, and keep an offline itinerary without claiming live proprietary availability.
Make the first run work locally with one documented command.
Store all user data locally by default and make export straightforward.
Put secrets in .env, ship .env.example, and never commit credentials.
Create trips, days, places, reservations, notes, documents, packing items, and emergency contacts.
Geocode only user-entered places and display them through MapLibre with cached trip-area tiles where allowed.
Parse forwarded reservation text locally into editable fields without logging message content.
Build a day timeline, route overview, conflict warnings, timezone display, and offline printable itinerary.
Allow manual updates for delays and reservations and label all external data with source and timestamp.
Export a complete trip bundle as JSON, calendar file, Markdown, and PDF.
Include clear empty, loading, success, and recoverable error states.
Add input validation, safe filenames, and graceful handling of unavailable APIs.
Write focused tests for the core transformation and one end-to-end happy path.
Create a README with setup, architecture, permissions, data location, and backup steps.
Do not add accounts, billing, telemetry, analytics, or a hosted control plane.
Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure.
Deliberately leave out live flight, hotel, award, or ticket inventory.
Deliberately leave out commercial turn-by-turn navigation and global offline maps.
Deliberately leave out booking guarantees, disruption rebooking, and traveler support.
Finish by running the tests and listing the exact commands used.