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Process · 01 Diagnose

Most AI projects start with a tool.
We start with the diagnosis.

Every engagement opens with the AI Workflow Audit — a structured read of how your revenue and operations run today, and where intelligent systems would create real leverage. Nothing gets built until we both see it clearly.

01Diagnose 02Architect 03Implement 04Optimize
Why This Phase

You can't automate what you haven't mapped.

Most AI work fails because it's pointed at the wrong problem — a tool bought before anyone agreed on what should actually change. The Audit removes that risk. We spend the first phase understanding how your revenue and operations genuinely run, so every decision after it is grounded in your business rather than a generic playbook.

It also means you get value before committing to a build: even if we never write a line of code together, you leave with a clear, honest read of where AI does — and doesn't — belong in your operation.

In This Phase

What the Audit covers

Four moves, run in sequence — from mapping what exists to a ranked plan of where to start.

01
Stack & data mapping

We document the tools in use, where data actually lives, and how it moves between them — the real system, not the org chart.

02
Workflow & handoff tracing

We follow the work across teams to surface the manual steps, re-keying, and handoffs quietly absorbing your team's hours.

03
Leverage analysis

We test each workflow against where AI genuinely helps — volume, repetition, data readiness, and risk — and flag where it doesn't.

04
Opportunity sizing & sequencing

We rank the opportunities by impact and effort, and lay out the order that compounds fastest — your roadmap to the next phase.

The Deliverable

AI Workflow Audit

Not a slide deck of generalities — a working document specific to your operation, written so the whole team can act on it. Five parts:

  • 01
    Current-state map — your stack and how data actually moves through it.
  • 02
    Manual-work inventory — the workflows eating time, with the cost behind each.
  • 03
    Leverage assessment — where AI fits, where it doesn't, and the reasoning either way.
  • 04
    Sequenced roadmap — a recommended first build, and the order that compounds.
  • 05
    Plain-language summary — one read your whole team can align on.
You own it · yours to keep, build or not
AI Workflow AuditScanning
Lead routingHigh leverage
Follow-up sequencesAutomate
Pipeline reportingHigh leverage
Quote & proposal draftingHigh leverage
Data entry & syncAutomate
Onboarding handoffAutomate
Deal-desk approvalsLeave as-is
High leverage Automate Leave as-is
What It Answers

The questions this phase settles

Where is your team's time actually going?
A clear read on the hours manual work absorbs — by team and by workflow.
Which workflows are ready for AI — and which aren't?
An honest readiness call on each, so you don't automate the wrong thing.
What's the highest-leverage place to start?
The one workflow where a first build returns the most, fastest.
What would a realistic first build take?
Its scope and shape — so there's no guesswork before you commit.
Where does AI not belong?
The work better kept with people, named explicitly — so the plan stays honest.
How do the pieces connect?
How a system would sit across the tools you already run, end to end.
What This Looks Like

Clear roles, no surprises

What we do
  • Interview the people who actually operate revenue and ops
  • Map your stack, data flows, and handoffs first-hand
  • Pressure-test each workflow against where AI earns its place
  • Produce the findings, the roadmap, and a clear recommendation
What you bring
  • Access to the team that runs the work day to day
  • A look at the tools and data you already use
  • A handful of conversations — the analysis is on us

Get Started

Start with the
AI Workflow Audit.

Book an AI Systems Review and we'll run the first read of your revenue and operations — and show you exactly where AI earns its place.