Power BI dashboards
Built around the decisions you actually make, not every metric available. Fewer numbers, better chosen.
Process Automation
We map the manual work inside your operation, automate it with Power Automate, Excel and AI-driven workflows, and measure the hours it gives back.
- Journal entries, reconciliations and the monthly close
- Invoices, reports and approvals that run themselves
- Built inside the tools you already pay for
- Hours and error rate measured before and after
U.S. Company and Tax
Formation, EIN, ITIN through an IRS-authorized Certifying Acceptance Agent, the company and personal returns, and the bookkeeping underneath them.
U.S. Company FormationITINBusiness Tax ReturnsPersonal Tax ReturnsAccounting and BookkeepingOperating and Tax BlueprintIFRS Financial Statements
Quote your case Global Talent
Vetted remote professionals, full time, by deliverable, by the hour or by project. They stay on our payroll, not on yours.
CAD and Site PlanningAccountingFinance and FP&AData AnalysisSystems and Software EngineeringAdministrative SupportProject ManagementCustomer Support
See all roles Business Intelligence
We turn scattered spreadsheets and systems into SQL data models and Power BI dashboards your team actually uses to make decisions.
- One source everyone reads from
- Dashboards built around decisions, not every metric
- Refreshed on their own, not rebuilt on Mondays
Training and Workshops
Workshops and coaching for finance teams on automation, Power BI and SQL, IFRS and running a U.S. company from abroad, built on your own files.
- In your office, live online or at your event
- Single sessions or packages of four to six
- In Spanish or English, on your own files
04 · Business Intelligence
Decisions, not spreadsheets.
Most companies do not lack data. They lack one place where the numbers agree with each other and update without somebody rebuilding them by hand.
Before and after
From the file nobody trusts to a number you can decide on.
On the left, the spreadsheet every company has. On the right, what the same data looks like once it has been cleaned, modelled and put somewhere everyone reads from.
Before
| A | B | C | D | E | |
|---|---|---|---|---|---|
| 1 | Cliente | Fecha | Monto | Estado | Vendedor |
| 2 | ACME S.A. | 03/04/2025 | 1.240,00 | pagado | M. Ruiz |
| 3 | ACME SA | 2025-04-03 | 1240 | Pagado | Maria Ruiz |
| 4 | Delta Corp | 04-13-25 | 890.50 | PAGADO | |
| 5 | Orion Ltd | 15/04/2025 | #N/A | pendiente | J. Pena |
| 6 | Orion Ltd. | 15/04/2025 | 2.100,00 | Pendiente | J. Peña |
| 7 | Vega SRL | 760,00 | ? | M. Ruiz | |
| 8 | Nexo | 28/04/2025 | 1,150.00 | pagado | C. Soto |
- The same client written three ways, so it counts as three
- Dates in three formats, and one of them is American
- Amounts with commas, dots and one #N/A
- Each salesperson keeps their own copy
After
$248kBilled
$31kOverdue
42 dDays to collect
Billed by month
Collected against billed
One source, one definition of “client” and one of “paid”, refreshed on its own. The numbers above are an example, not a client’s.
The symptoms
You probably recognise at least two of these.
- •Two people, two numbersFinance and operations quote different figures for the same month, and the meeting becomes a debate about whose file is right.
- •The report is stale by WednesdayIt is accurate the day it is built, so people stop trusting it and go back to asking around.
- •One person owns the spreadsheetWhen they are on holiday, reporting stops. That is not a reporting problem, it is a risk.
- •Decisions wait for dataBy the time the number arrives, the window it was meant to inform has closed.
What we deliver01 02 03 04
A model your team can run without us.
One source of truth
Connected to your systems so the figures refresh themselves. No copy-paste step anywhere in the chain.
Operational and executive views
Daily detail for the people running the work; the handful of numbers that matter for the people steering it.
Handover and training
We document the model and teach your team to extend it. You are not buying a dependency.
How we work
Questions first, data second.
We start from the decisions you need to make, then work backwards to the data required. That order matters: dashboards built from whatever data happened to be available are the ones nobody opens twice.
It also tends to surface the real problem. More than once the answer has not been a dashboard at all, but a process that was producing bad data in the first place — which is where our automation work picks up.
Financial data strategy
Before the dashboard, a decision about the data.
Some companies do not need another report yet. They need to agree on what their data is: where each figure comes from, who owns it and how it is defined. That is financial data strategy, and it is what makes dashboards, automation and decisions hold up.
01
Inventory
Every source of financial data, what it holds and how far it can be trusted.
02
Definitions
One definition of revenue, margin, customer and paid invoice, written down and agreed.
03
Architecture
Where the data comes together, in SQL or in the tools you already have, and how it refreshes.
04
Roadmap
What to build first to cut costs and gain control, in order, with a rough cost for each step.
As a project, or as a monthly advisory with a fixed number of hours, for companies that want someone senior watching their numbers.
SQLPower BIPower QueryDAXExcel
Questionnaire
Tell us about your data.
Seven questions about where the numbers live and who reads them. Most of the effort in a dashboard is underneath it, and this is how we size it.
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Tell us the decision you cannot get a straight number for.
That is usually the right place to start.