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PacketLens

See which required documents arrived, which still need review, and why a packet is not ready.

Concept illustration of PacketLens workflow; no live customer data
Project
PacketLens
Audience
Procurement, supplier onboarding and service teams collecting recurring document sets
Type
Independent working prototype
Evidence
Repository, documentation and tests

Where work gets stuck

Teams often chase attachments across inboxes without a shared view of what is missing, expired or approved by a person.

This project is for procurement, supplier onboarding and service teams collecting recurring document sets. The aim is to make the next decision visible to the people doing the work.

What a team might do

A supplier sends registration, tax and insurance files. The system suggests categories from text, but a reviewer checks the originals. Two items are approved; the insurance certificate is expired. The packet remains not ready until a valid replacement has been reviewed.

What the prototype does

  • Document intake and transparent category suggestions
  • Human approval, expiry checks and review history
  • CSV report and packet deletion

What I built and tested

I designed and implemented this independent prototype to explore the business workflow and its technical constraints. Python API, PDF/DOCX/TXT text extraction, validation, storage boundaries and tests. The repository explains how to run its real implementation and tests.

Explore the demo and the code

Open the fictional browser walkthrough to understand the workflow. Read the source and README for installation, local testing and implementation details. The browser page does not run the backend service.

What this version does not claim

The Pages walkthrough is fictional. The local Python prototype does not provide OCR, cloud hosting or company user accounts; it does not verify legal authenticity. No customer outcomes have been measured for this independent demonstration.

Could this fit your team?

Map a three-document onboarding packet with fictional files and let reviewers identify where the current process becomes unclear. There is no fee or obligation to adopt a product. Any work involving real data or a production deployment would need a separate scope and appropriate safeguards.

Tools and skills

PythonFastAPIDocumentsReview

What document is most often missing when work is ready to begin?

Tell me how your workflow currently works. We can explore a small guided pilot or discuss a software system tailored to your organization.

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