Trace Lantern

Offline evidence kits for digital work

Make the handoff
stand up to inspection.

Practical, local-first tools for checking AI-built MVP launches and source-code deliveries—without uploading repositories, credentials, or customer data.

Explore the kits Email support

Private preview · No live checkout

TRACE / VERIFY / HAND OFF

Evidence before confidence.Local tools. Explicit limits. Reviewable outputs.

Two focused toolkits

Built for the moment when “it works” is not enough.

Each kit turns a vague acceptance decision into a documented, reviewable process.

Preview of the AI MVP Launch Readiness Kit

01 / LAUNCH READINESS

48-Check AI MVP Launch Readiness Kit

An offline workbook for Next.js and Supabase projects covering authorization, RLS, build evidence, deployment ownership, backup, rollback, and handoff.

  • 48 evidence-backed controls
  • Pass, Fail, Blocked, N/A, and Not checked states
  • Formula-driven launch decision and retest log
Private test preparation
Preview of the Source-Code Handoff Acceptance Kit

02 / SOURCE HANDOFF

Offline Source-Code Handoff Acceptance Kit

A local Python inventory scanner and structured templates for checking whether a web-project delivery is complete, reproducible, and transferable.

  • Standard-library repository scanner
  • 14-area acceptance checklist and risk register
  • Ownership, environment, and AI-component transfer matrices
Private test preparation

How Trace Lantern works

Useful boundaries are part of the product.

01

Local by default

Source code, API keys, credentials, and customer data stay on your system.

02

Evidence, not theatre

Unknown and blocked items remain visible instead of being converted into optimistic claims.

03

Honest scope

The kits organize review evidence. They do not certify security, ownership, or production safety.

Questions or product access

Contact Trace Lantern support.

tracelantern@outlook.com