Building AI-Native Mexican Fiscal Compliance: 7 Months Solo
May 5, 2026
I built an AI-native Mexican Fiscal Compliance-as-a-Service platform. Solo. 7 months. No co-founder to blame.
Yeah, I know how that sounds. "AI-native" and "fiscal compliance" don't usually share a sentence, and when they do, it's usually weekend vibecoded trash wrapped in a Vercel template with a ChatGPT API key and a $299/month price tag. I wouldn't have believed it either.
But here's the thing: Mexican fiscal compliance (CFDI 4.0, SAT, EFOS/EDOS) is one of the most structured, rule-dense, high-stakes domains in business operations. Which makes it a perfect fit for AI - if you actually engineer it instead of prompt it.
So starting this week, I'm publishing a series on the architectural decisions behind DISAI-Conta. Not marketing. Not demos. The actual decisions:
- How I route 80% of requests away from expensive models without degrading quality
- How I handle CFDI validation, EFOS blacklist monitoring, and CSD state - reliably, at scale
- How a solo founder builds enterprise-grade infrastructure without an enterprise budget
- The tradeoffs I made, why I made them, and what I'd do differently
If you're building serious AI products, working in Mexican finance/accounting, or just want to see what "AI-first" looks like when it's engineered and not vibed, follow along. First post drops tomorrow.
Prompts are architecture decisions. This series is the proof.
Originally published on LinkedIn.