Nine small, focused tools that each solve one quick supply chain or data science problem — the kind of recurring "micro-inconvenience" that rarely gets its own project but eats time every week. Built fast, with AI, to prove a point: I notice these bottlenecks, and I can go build the fix instead of just flagging it.
Most operations and data work isn't glamorous — it's a dozen small decisions made well or poorly: when to reorder, how much to order, whether a supplier is actually reliable, whether that A/B test result is real. Each tool here targets exactly one of those decisions and makes it a ten-second calculation instead of a spreadsheet exercise nobody has time for. That's the kind of problem-solving I want to bring to a team: spotting the friction and removing it.
Know exactly when to reorder — before you're out.
Find the order size that costs the least.
What a product actually costs once it's in your hands.
Find out which 20% of your SKUs actually matter.
Log shipments, see which suppliers actually deliver on time.
Paste a CSV, get an instant data health check.
Paste a column of numbers, instantly see what doesn't fit.
See which simple forecasting method actually wins.
Is that lift real, or just noise?
The supply chain formulas in these tools (safety stock, reorder point, EOQ, ABC analysis) and the AI-native approach to building them both come from real coursework, not just a Google search: