Do we need to have our systems documented before we start?

No. Part of the Discover phase is mapping what you have. Most clients don’t have full documentation — that’s usually part of why they’re talking to us.

What tools and platforms do you work with?

We work across the major data platforms, CRMs, ERPs, and warehouse tools. The specific stack depends on what you’re already using. We fit around your environment, not the other way around.

Is there a long-term contract?

No. Month-to-month with 30-day cancellation notice.

How is this different from hiring a data consultant?

A consultant delivers a recommendation and moves on. We build it, harden it, document it, and stay involved. You leave with something that runs, not a slide deck of suggestions.

Clean and Structured Data

Your AI is only as good
as the data behind it.

Every AI project in your organization is only as reliable as the data it runs on. Most organizations are sitting on data they cannot actually use. Garbage in, garbage out — your AI tools, dashboards, and automations will underperform until the data underneath them is clean, structured, and integrated. We build that foundation, and we build it so every system downstream can depend on it.

Start the Brief

Free data audit, NDA included

No commitment, no lock-in

Data Integration

Connect siloed CRMs, ERPs, and warehouses

Pipeline Setup

Scheduled ETL, incremental loads, error handling

Schema Design

Clean, consistent, automation-ready structures

Data Audits

Map what you have, surface the real gaps

Governance & Access

Controls, audit logging, and docs from day one

Live Dashboards

Reports that refresh on a schedule, not on request

17+ Years Placing Specialists

|Foundation Layer

|Month-to-Month

|No Lock-In

What We Typically Find

Sound familiar?

Before we recommend a pipeline, a schema, or a dashboard, we look at what is actually running today. This is what we find on almost every first engagement.

Critical data lives in siloed systems that don’t talk to each other
Reports are assembled manually, usually in spreadsheets, by people with better work to do
AI and automation projects stall because the underlying data is too inconsistent to trust
No single source of truth — different teams are working off different numbers on the same day

How We Deliver

Every engagement follows the same five stages.

Some clients move through it in weeks. Others take a more measured pace. Either way, the approach never changes. No surprises. No black boxes. Always a clear next step.

Talk to the Team

Discover

We map your systems, walk your workflows, and identify where the real problems — and the real opportunities — are hiding. Most clients are surprised by what we find.

Define

A clear outcome, a measurable goal, and a shared understanding of scope. This is the stage that keeps projects from drifting — and keeps relationships intact.

Build

We build in stages so you can see progress, give feedback, and course-correct before anything is set in stone. Every checkpoint is something real you can use.

Harden

We make sure everything we build is secure, documented, tested, and fit for your production environment — and for the clients or teams who will depend on it every day.

Scale

Every engagement ends with a decision. Either way, you leave with something that works, a team that understands it, and a clear path forward.

What You Walk Away With

Outcomes you can point to.

Not a slide deck. Not a recommendation. Working data infrastructure your team can rely on from day one — with everything documented so the next person can pick it up.

A single source of truth

One place where every team looks up the same number. No more “which report is right?” conversations before every meeting.

Automation-ready data

Clean, consistent schemas that downstream automations and AI workflows can depend on without breaking at edge cases.

Governance built in from the start

Access controls, audit logging, and documentation from day one — not retrofitted after something goes wrong.

Dashboards that refresh automatically

Reports that update on a schedule instead of waiting for someone to pull, clean, and format a spreadsheet every week.

Ideal For

Who typically starts here.

Ideal Industries

Financial services and accountingHealthcare operationsLegal back-officeReal estate and property managementE-commerce and D2C brandsMarketing ops teams

Who Initiates the Conversation

Data analysts and reporting leads
Responsible for reporting but blocked by data that is inaccessible, inconsistent, or manually maintained.
Operations managers
Teams spending hours per week pulling, cleaning, and formatting data before it can be used for anything.
CTOs at growth-stage companies
Multiple systems acquired through growth, none integrated, all siloed, and the debt is compounding.

Common Questions

Frequently Asked Questions

Have a specific question?

Talk to our team and we'll walk through your data stack together.

Talk to the Team

It depends on scope. Most data audit and pipeline engagements move from scoping to a working first deliverable in a few weeks. We build in stages so you’re not waiting on a big reveal.