All projectsAutomation · Internal product tooling

Real project

A month-long onboarding process, cut to 3–4 days.

A desktop workflow that coordinated APIs, HS-code configuration, metadata validation and scheduling so new products and countries could move faster.

30 → 3-4days to onboard
The problem
Adding a new product or country meant repeating setup across mappings, metadata and scheduling by hand. It took about a month each time.
What I built
A desktop tool that guides the user through each step, validates the metadata and calls the platform APIs.
My role
Mapped the full process, built the interface and the API integration. Junior Data Analyst.
Result
About 30 days → 3–4 days per onboarding, roughly 26 days saved each time. Errors caught before handoff.
Why it was hard
  • Many dependent setup steps across several systems
  • Existing API and platform constraints
  • Non-technical users, with business mappings still needing analyst approval
Tools
Python · Tkinter · REST APIs · metadata validation
Team collaborating around a laptop in an office
Illustrative photo.

THE PROBLEM

Why the system needed to exist.

Onboarding required repeated setup across mappings, metadata and workflow scheduling. The work was technically precise but fragmented, slowing delivery and increasing the chance of omissions.

MY ROLE

Where I created leverage.

I mapped the full operational sequence, built the internal interface and integrated the existing platform APIs into a guided, validated workflow.

SANITIZED WORK SAMPLE

One guided path replaces a fragmented checklist.

The operating sequence is shown at capability level; internal endpoints, screens and identifiers are deliberately excluded.

01 / REQUESTPRODUCT + COUNTRY

The workflow starts with a bounded onboarding request and required ownership.

02 / GUARDRAILSHS CODE + METADATA + API CHECKS

Required configuration is validated before anything is scheduled.

03 / HANDOFFREADY / REVIEW / BLOCKED

Clear states expose the next action instead of hiding failures in logs.

Simplified workflow reconstruction based on verified responsibilities and turnaround outcomes.

Technical details

SYSTEM FLOW

From friction
to a repeatable flow.

  1. Product request
  2. HS-code setup
  3. Metadata generation
  4. API validation
  5. Workflow scheduling
  6. Readiness checks
  7. Handoff

CONSTRAINTS

The difficult parts.

  • Multiple dependent setup steps
  • Existing API and platform constraints
  • Business mappings requiring analyst validation
  • A non-technical internal user experience

DESIGN DECISIONS

How I approached them.

  • Turned a checklist spread across systems into one guided workflow.
  • Validated metadata before submission so errors appeared close to their source.
  • Kept analyst approval for business-sensitive mappings while automating mechanical work.
  • Designed clear progress and error states for repeatable team use.

OUTCOMES

Project outcomes

3-4 days

typical delivery

Reduced from roughly one month.

One flow

instead of fragments

Setup, validation and scheduling in one tool.

Fewer gaps

before handoff

Required metadata checked earlier.

TECHNICAL SURFACE

PythonTkinterREST APIsMetadata modelingWorkflow automationValidation
NEXT SYSTEM / 04

Finding the same ship under different names.