Services · Data & Analytics

Know your numbers.

Dashboards that get used, reports that write themselves, and pipelines that pull your tools into one source of truth. Built by a team that has run data platforms at scale, sized for your business.

In practice

One place where the numbers agree.

Sales lives in one tool, marketing in another, operations in spreadsheets, and every report disagrees. We pipe them into one model and put the answers on one screen: refreshed automatically, trusted by everyone, checked for quality on every sync.

What we build

Six ways data starts paying rent.

01

Dashboards & reporting

One screen for the numbers that matter, refreshed automatically, readable without a data team.

02

Reporting automation

The Monday-morning report that takes someone four hours now takes zero: generated, checked, and delivered on schedule.

03

Pipelines & integrations

Your CRM, billing, and ops tools wired into one source of truth, synced on schedule, with quality checks built in.

04

Spreadsheet replacement

The workbook that secretly runs the business, rebuilt as a real tool: history, permissions, validation, no broken formulas.

05

Customer & sales analytics

Who buys, what repeats, where the margin hides: questions your existing data can already answer once it's in one place.

06

AI-ready data

Clean, structured, and retrievable: the groundwork that makes AI automation answer correctly instead of confidently guessing.

Questions

Fair questions.

No, and it's sized accordingly. Most of our data work is for businesses with a handful of tools and a pile of spreadsheets, not enterprises. A focused dashboard or one automated report is a small, fixed-scope project, and it usually pays for itself in recovered hours within months.

That's the normal starting state, and cleaning it up is part of the work, not a precondition. We've untangled duplicate customer records, inconsistent product names, and exports that disagree with each other. The deliverable includes the cleanup and the checks that keep it clean.

Proven, boring-on-purpose ones: SQL databases like Postgres, warehouses like Snowflake when the scale calls for it, dbt for transformations, and either your existing BI tool or a lightweight dashboard we build into your site or internal tools. You own all of it, accounts, queries, and pipelines included.

Often not. For many businesses a well-modeled Postgres database and a scheduled sync cover everything. We size the architecture to the data you have and the questions you ask, and we'll tell you plainly when the bigger setup isn't worth the money.

Directly: AI answers are only as good as the data behind them. Retrieval, automation, and reporting agents all need clean, structured sources. Data work is frequently phase one of an AI project, and doing it once serves both.

Scoped like everything we do: a written scope and a fixed price for defined work, or a monthly arrangement for ongoing reporting and pipeline upkeep. Most engagements start with one dashboard or one automated report, small enough to prove the value fast.