The “Aha!” Behind LayerNEXUS

It’s 11:47 pm, i’m six coffees in, and i’m staring at a file called
client_data_FINAL_really_FINAL_v7 (1).csv.

Sound familiar?

Marketing dumped their CRM, ops spat out an airtable export, finance sent a “quick spreadsheet” (30 MB, cheers). duplicate columns, random NULLs, zero keys. i’m supposed to build a dashboard by… tomorrow?

that’s when it hit me:

the bottleneck isn’t analysis—it’s turning this spaghetti into a real database.

so instead of writing yet another cleanup script, i opened a fresh repo and scribbled:

upload csv ➜ auto-detect relationships ➜ spit out clean SQL + ERD

three late-night commits later the prototype chewed through my nightmare dataset in minutes. no manual joins, no hand-drawn ER diagram, no “just one more script.”

I called it LayerNEXUS. because it glues the raw layer (your ugly CSVs) to the useful layer (a proper, normalized schema).

Stop drowning in exports. Start shipping insights.