-
-
RFQ management
-
SQDC supplier scoring
-
Derisking new supplier
-
Cost avoidance tracking
-
Supplier dashboard
-
RFQ KPI analysis
-
Savings KPI analysis
Inspiration
DataFlow started from a very practical problem I experience in procurement work: information is often scattered across spreadsheets, emails, notes, supplier lists, RFQs, and manual reports. I wanted a simple local tool to keep operational data organized without starting a complex ERP project.
What it does
DataFlow is a lightweight desktop application for procurement workflows. It helps manage RFQs, supplier data, savings, cost avoidance, risk tracking, KPIs, global search, and Excel exports. The goal is to give a buyer a clear operational view of their work from one local application.
How I built it
I built DataFlow as a Python desktop app using Tkinter and local data storage. Development was strongly assisted by ChatGPT and Codex through iterative prompts, code reviews, scoped refactoring, testing, and UX adjustments. My focus was stability, simplicity, and practical workflows.
Challenges I ran into
The main challenge was keeping the application useful without making it too complex. Procurement workflows can grow quickly, so every feature had to stay focused and reversible. Another challenge was improving the user experience while preserving compatibility and avoiding unnecessary dependencies.
Accomplishments that I'm proud of
DataFlow became a real working application, not just a mockup. It includes multiple procurement modules, KPI views, search, and export features. I’m especially proud that it was built from a real business need, with AI assistance used as a development partner rather than just a code generator.
What I learned
I learned that AI-assisted development works best when the human provides strong domain knowledge, clear constraints, and careful validation. Codex was most useful when tasks were scoped, risks were explicit, and each change could be tested before moving forward.
What's next for DataFlow Procurement Software
Next steps include improving data validation, refining the UI, adding more reporting options, strengthening backup and import/export workflows, and preparing a more polished release. Longer term, DataFlow could evolve into a practical toolkit for individual buyers and small procurement teams that need control without ERP complexity.
Log in or sign up for Devpost to join the conversation.