Run the business on numbers you can finally trust.

Decisions get made every week. The numbers behind them live in five systems and a spreadsheet someone updates by hand. A senior fractional data team builds the layer that puts the whole business on one screen, current every morning.

01 Sound familiar

How decisions feel without a data layer.

Two reports disagree, and the meeting turns into a debate about whose spreadsheet is right.

→ one source of truth

A bad month surfaces three weeks after it ended, when the options for fixing it have already expired.

→ live dashboards

The numbers exist somewhere. Getting them means asking a person, waiting two days, and asking again.

→ self-serve reporting

One person knows how the revenue report gets built. The company holds its breath when they take a week off.

→ owned pipelines

02 What we build

A data layer, not a pile of charts.

Four pieces, built in your accounts and connected end to end, so every number traces back to a source.

Unified dashboards

CRM, billing, operations, and marketing in one live view. The number you check at 7 a.m. is the same number your team works from all day.

Pipelines and ETL

Collection, cleaning, and reconciliation run overnight without a human in the loop. Data moves itself; people read results.

A warehouse you own

One governed source of truth in your own cloud, modeled so the next business question is cheap to answer instead of a new project.

Reports and alerts

Weekly reports that build and send themselves, and alerts that fire the moment a number crosses the line you set.

The tooling

Built on the same tooling Fortune 500 data teams run, in plain language and plain SQL. Your data never leaves your accounts.

Python · SQLPostgres · BigQueryDatabricksPower BIETL / ELT pipelinesYour cloud, your accounts
03 Proof

What the data layer did for a recruiting company.

Recruiting operationsUS-LATAM
3 systems unified · AI matching inside

Three disconnected systems became one answer.

Emerald Inc. connects US companies with top LATAM talent. Their recruiting data sat in three platforms that never agreed, and candidates moved between them by hand. Forja unified everything into one portal where AI matches candidates with open roles on top of clean, connected data. The volume ceiling came off without adding headcount.

“Emerald cut candidate delivery from 7+ days to 48 hours without hiring more recruiters.”

Ben Davis, Emerald
Read the Emerald story
2,000+ hours a year returned to client teams
40% average operational efficiency gain per business
4 years building data systems across the Americas
04 How it runs

A data team, sized to your need.

The fractional model: senior data practitioners on your problem, scoped by project, without the full-time payroll.

A named senior lead

The analyst who scopes your data layer is the one who answers when a number looks wrong. Context never gets lost in a handoff.

First numbers in weeks

The first connected dashboard lands early, then the layer grows source by source. You see value before the full build is done.

You own the layer

Warehouse, pipelines, and dashboards live in your accounts. If we disappeared tomorrow, your numbers would still update.

Engagements start within two weeks.

05 Common questions

Frequently asked questions.

What does a data intelligence engagement deliver?

Dashboards that put CRM, billing, operations, and marketing in one live view. Pipelines that collect and clean data overnight without a human in the loop. A governed warehouse in your own cloud. Reports and alerts that build and send themselves. Every piece lives in your accounts, so the numbers keep updating whether or not we are in the room.

Our systems never agree with each other. Can you still unify the data?

That disagreement is usually the starting point. Emerald Inc. ran recruiting data across three platforms that never matched, with candidates moved between them by hand. Forja unified everything into one portal on top of clean, connected data, and the volume ceiling came off without adding headcount. Reconciliation runs inside the pipeline, so the numbers agree by design instead of by someone checking.

How soon do we see the first working dashboard?

The first connected dashboard lands within the first weeks, not at the end of the project. The layer then grows source by source, so you work from real numbers while the rest gets wired. Engagements start within two weeks of scoping.

Do we need a data warehouse to get started?

No. Engagements start with the number you most need to see, usually a live dashboard connected to the systems you already run. The warehouse comes when the business questions outgrow direct connections, and when it does, it gets modeled in your own cloud as one governed source of truth.

// Let's talk

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