Custom Software · Data & Reporting

Numbers you can trust. Systems that talk.

Data foundation, integration, reporting and dashboards, operational visibility. When the month-end close takes five days or three reports disagree, the problem isn’t the report — it’s underneath it. Starts with a System Evaluation.

Sound familiar?

If you’ve said any of these out loud lately.

  • Three reports, three different revenue numbers, one board meeting.
  • Month-end close takes a week because someone reconciles by hand.
  • The data is in the systems. Getting it out is a project every single time.
  • We bought a BI tool. It made the arguments prettier.
  • Everyone wants AI on our data. Our data isn’t ready for a spreadsheet.
What we do

Four moves. In this order.

01
Map where the truth lives
Every system, who owns it, and what each metric actually means. Most “data problems” are definition problems wearing a costume.
02
Build the foundation
Integrations that run on a schedule instead of on a person, a governed data layer, one definition per number. Boring on purpose.
03
Report what runs the business
Dashboards people open every morning and alerts that fire before the customer calls — not 40 charts nobody trusts.
04
Make it AI-ready
The same foundation feeds automation and agents. Once the numbers are trustworthy, AI Office can build on them.
What it costs to start

One priced first step. Then a real proposal.

The entry offer

System Evaluation

Fixed fee · from $3,500

An independent read on your systems, your data flows, and what’s actually blocking one version of the truth — with a prioritized plan and a fixed proposal for the foundation work.

  • Systems, integrations, and data flows mapped
  • Where definitions diverge and reconciliation happens by hand
  • Data quality and ownership gaps, prioritized
  • A fixed proposal for the first slice of foundation

Before you call: How to compare system integration companies · Value-at-Stake Calculator — size the prize before you build · What it costs · How we work

What clients say

Partner, not vendor.

You guys really exceeded my expectations. The understanding the team has of our complex business is impressive. We’ve come a long way and you guys made it happen.
Omer Khan, Senior Director of Technology, K2 Integrity
Everyone was so thrilled about having a modern system that’s easy to log into, and everyone was happy with the reporting. We almost didn’t have to do any training anymore because the system was intuitive.
Doak Dunkin, EVP of Operations, Dunkin & Associates
Pre-project consulting

Five steps, every time.

For data & reporting, “Engage” means the System Evaluation first — then the project, on the engagement model we recommend after it.

  1. 01
    Discovery Call
    30–60 min

    You tell us the problem in your words. We tell you straight whether — and where — we can help. No slides.

  2. 02
    Deep Dive
    60–90 min

    The people closest to the problem, in one room (or one call). We get to the real constraint and the number that matters.

  3. 03
    Proposal & Paperwork
    days, not weeks

    Scope, price, and timeline in writing. A standard MSA and a short SOW — no 50-page lock-up.

  4. 04
    Prep & Kickoff
    week 1

    Access, environments, and a kickoff with everyone who touches the work. You know who’s on it and what ships first.

  5. 05
    Engage
    ongoing

    The work itself — visible every week, in your environment, with your people in the loop.

The full picture on how we work →

Questions about data & reporting

Straight answers.

Do we need a data warehouse?

Sometimes. Often the first, biggest win is integration plus a governed layer with one definition per metric — a warehouse comes later if the volume or the questions demand it. The evaluation tells you which.

Which BI tool should we use?

The one your people will actually open. We’re tool-agnostic and have built on most of them; the tool is rarely the problem. The data underneath it usually is.

How is this different from AI Office?

AI Office automates workflows on the systems you already have — and a data-readiness build is often the very first one. When the foundation itself is the project — integrating fifteen systems, standing up a governed data layer, rebuilding reporting end to end — that’s software development, and it starts here.

Can you fix our data quality?

We fix the causes: ownership, definitions, and integrations that create bad data in the first place. Cleaning symptoms without fixing causes is how you end up buying a second BI tool.

Is this the foundation for AI?

Yes. Agents and automation act on your data; if the data is wrong, they’re confidently wrong at scale. Most AI programs that stall did so here. Doing this first is how you avoid being one of them.

Get started

One version of the truth starts with an honest look.

A System Evaluation is a fixed fee. Book a 30-minute intro and tell us which number nobody in the building trusts.