Data mining and AI from the inside, no fluff.
I spent years moving between large companies like Microsoft and early-stage startups. On both sides I kept seeing the exact same pattern: back-office work eats most of a team's time, and almost all of it is repetitive. People don't fall short because they lack judgment. They fall short because they're handling tasks the tooling should be doing on its own.
The fastest way to get a worker (and a business) operating at 100% is removing the friction between the tools they already use and the outcomes the company actually needs.
That's where DataQuimbaya comes in: we study your data so we can act on it, not just report it. We design the flow, connect the pieces, and leave the human deciding what only a human should decide.
Human-in-the-loop by default
AI accelerates, it doesn't replace judgment. I design flows where the critical final call always stays with a person.
Solutions, not platforms
If an existing tool solves the problem, we use it. If not, I build just what's needed, no over-engineering.
Real measurement, not promises
Every automation ships with metrics: hours saved, conversion lifted, errors reduced. If it doesn't move a number, we don't charge for it.
The change is not abstract. It is hours and dollars.
This is the first project DataQuimbaya was born from. Before founding the company, our founder was one of 10 lifecycle managers at a company with a sales organization of 250+ people. Each of them had 20 SDRs booking their meetings. He built the system that prepared everyone's day: it prioritized inbound email, created the tasks, ranked the opportunities so SDRs knew who to call first, and wrote the prep notes for each meeting: what the company does, where it hurts, what to ask.
One working day, before and after
From a system our founder built in a previous role, for a sales organization of 250+ people. Your operation is different: we measure yours in the diagnostic.
How many extra jobs a month does this need to bring in before it pays for itself? Bring your average ticket to the call and we work it out with your numbers, not ours.
Four things we do differently.
We speak your language, not engineering.
You get decisions and processes that run on their own, not dashboards. At the end of each project you know what changed in your operation, not which technology was used.
We work inside your systems.
Not from the outside with a PDF of recommendations. We go into your CRM, your spreadsheets, your WhatsApp, and your invoicing, and build right there.
Results measured in hours and dollars.
Over 4 hours a day of manual work removed across a sales team of 250+ people. It was the first project DataQuimbaya was born from.
See the numbersThe system is yours.
Documented, in your accounts, and not dependent on us to keep running. It is what a big company demands from a vendor and a smaller one almost never gets.
Technical stack
I'm fluent in:
- Automation and orchestration: n8n self-hosted, Make, Zapier, and custom code when the flow outgrows them
- Languages: TypeScript/Node.js, Python, SQL
- AI: Claude API, OpenAI API, RAG assistants trained on your data, voice agents with ElevenLabs
- Data, CRMs, and infra: Postgres, Supabase, HubSpot, Pipedrive, Salesforce, deployments on DigitalOcean
- Integrations: REST APIs, webhooks, WhatsApp Business API, Slack, Google Workspace