FINANCE, DATA AND AI · FULLY REMOTE
Your board wants AI in the finance function. Your data isn't ready.
Most mid-market companies run finance on spreadsheets and disconnected systems, then wonder why every AI pilot stalls. The foundation comes first, then the FP&A that runs on it. Ex-AWS EC2.
monthly-close · source status
From 12 days to 4| Source | System | Status | Days |
|---|---|---|---|
| Accounting | ERP | Connected | 1 |
| Billing | In-house system | Connected | 1 |
| Operations | Spreadsheets | Manual | 6 |
| Banks | Statements | Manual | 4 |
Monthly close once all four sources are connected
4 days
5 years at AWS leading financial planning and pricing for EC2
One of the largest cost lines in tech
Monthly close cut 30% with Python automation
IF THIS SOUNDS FAMILIAR
The problem isn't your team. It's the foundation under it.
01
The close takes weeks
The numbers live in spreadsheets, inboxes, and one person's head. Every month-end is archaeology.
02
Your systems don't talk to each other
Accounting says one thing, billing says another, ops has its own version. Nobody sees a single source of truth.
03
AI pilots keep stalling
The tools work. Your data doesn't. Every AI initiative dies on the same rock: nobody built the foundation first.
04
Reports describe the past
You learn what happened last month, three weeks late. You never see what's coming. That's reporting, not finance.
BACKGROUND
Where the methodology was built.
5 yrs
Financial planning and pricing for AWS EC2
30%
Monthly close reduction through automation
15
Years across finance, operations and technology
AWS EC2
Amazon Web Services
Led financial planning and pricing for EC2 capacity, the infrastructure behind the AI buildout and one of the largest cost lines in tech. Built the pricing frameworks behind EC2's largest cost-savings programs and Python automation that cut monthly close by 30%.
Fractional finance and data
Consumer electronics distribution
Led the cloud migration and finance data build for a distributor operating across Argentina, Mexico, and the US. Databases, automated reporting, and FP&A rebuilt from the inside, alongside the monthly close and forecasting.
Automation stack
Health and sports performance
Fractional CFO and COO for a profitable operation running entirely through WhatsApp and Instagram, with no CRM and no structured data. Built the cash model, the P&L tracker, the client database and weekly KPI reporting, plus the automation stack design on n8n, the WhatsApp Business API and the Claude API.
ABOUT
Finance from inside the machine.
I ran financial planning for EC2 capacity at AWS, the infrastructure behind the AI buildout. My whole career is turning messy cost data into operating models leadership can plan against: at AWS that meant one of the largest infrastructure cost bases in tech, since then it has meant building that same capability inside mid-market companies. Foundation first, then the finance.
15 years across tech, finance, and operations. Goldman Sachs, PE-backed tech companies, Amazon.
Silver Andes is a personal practice. Enquiries by email. Fully remote, any time zone.
GET IN TOUCH
If your finance function runs on spreadsheets and one person's memory.
Write with a line or two about where your finance data lives and what you're trying to fix. No pitch deck, no forms, no funnel. If there's something worth talking about, we'll find a time.
or write directly to agustin.lastra@silverandes.com