How I'm helping businesses turn "data chaos" into "data clarity" (and saving 10+ hours/week)
I’ve been building custom automation systems for the past few years, and I’ve noticed a pattern: most businesses are bleeding time on manual lead research, messy Excel cleaning, and broken API integrations.
I’ve recently shifted my focus to building scalable, automated B2B pipelines for founders.
Here is my core tech stack for these automations:
Python: The backbone for custom scraping and bot logic.
API Integration: Connecting fragmented tools to remove manual workflows.
Data Enrichment: Cleaning messy datasets so they are actually actionable for sales teams.
I’m currently "Building in Public" my service offerings and would love to hear from other devs/founders: What is the most time-consuming "data task" currently stopping you from growing your business?
I'm looking to optimize more workflows, so if anyone is struggling with data bottlenecks, let's chat.
The strongest positioning would name the first operational decision the cleaned data improves. Saving ten hours is useful, but tying that time to faster reporting, fewer errors, or a revenue action makes the value easier to buy.
I've seen teams spend weeks enriching lead lists and wiring up integrations, then still end up making decisions from the same handful of signals they trusted before.
The messy part usually isn't getting more data into the system. It's that every new source creates another place where people can disagree about what's actually worth paying attention to.