AI systems, designed and built.

We find where AI moves your money. Then we build it and run it.

Not slide decks. Working software that reads your real data, does real work, and keeps running after we hand it over. Built for contractors, distributors, professional services firms and manufacturers.

We’ve been the client Every number from delivered work We’ll tell you when not to build
Weekly outreach · Commercial landscaping Live
  1. 01
    Read the inbox3,000 email conversations → 945 facts
  2. 02
    Apply the block listCompetitors and opt-outs removed before scoring
  3. 03
    Score every account out of 10083 opportunities in three priority tiers
  4. 04
    Draft in the owner’s voiceEach one names the properties that manager controls
  5. 05
    Owner approvalApprove, edit or hold every message
  6. 06
    Send and verifyEvery sent message checked against what was approved
Nothing sends until the owner approves.

From case 01, a commercial landscaping company. Live and running every week. Read it

The problem

The problem is usually the same.

You know AI matters. What’s missing is someone who can see where it actually moves your money, and then build it into the business.

01

Quoting is slow.

Prices go out late, or not at all, because one person holds the numbers.

How we fix itMap where the time goes, rank it by dollar impact, and prove the fix on your own data.

02

Follow-up leaks.

A quote with no reply gets written off as lost. Usually it’s an open opportunity.

Built and liveA system that ranks who to chase and drafts the message in your voice.

03

Admin keeps growing.

The office cost climbs faster than revenue, and the next hire is another admin.

How we fix itAn Assessment that prescribes the tools to win back 5–10 hours a week.

04

The core runs on spreadsheets and memory.

The customer record lives in a spreadsheet and one person’s memory. It held at the old size. Every new customer and hire breaks it a little more.

What we buildOne production system that runs the process on your real data. One build turned a 33-row spreadsheet into 120+ mapped contacts.

The work · Case 01 · Commercial landscaping

The next contract was already in the inbox.

Live · running every week

Years of property-manager relationships sat in two email accounts. The customer list was a 33-row spreadsheet. Nobody could say who was still warm, or who to call first on Monday.

  • Old relationships reopened and turned into booked meetings
  • Quote requests coming back from accounts that had gone silent
  • A weekly outreach campaign that runs without the owner doing any admin
  1. ~3,000Conversations

    It read the archive. Three and a half years of email with property managers: every quote, reply, meeting and outcome.

  2. 945Clear facts

    It turned them into facts, each one traceable back to the email it came from. A quote with no reply counts as an open opportunity, not a lost deal.

  3. 83Ranked accounts

    It scored every account out of 100 and ranked the opportunities in three priority tiers. Competitor-linked firms and opt-outs were blocked before scoring.

  4. 120+Contacts mapped

    It rebuilt the customer list from 33 contacts to over 120: which properties each manager controls, when they were last contacted, what was quoted.

  5. OwnerApproves every message

    It writes like the owner, modelled on his own past emails. He approves, edits or holds every message. The system cannot send on its own, and every sent message is checked against what he approved.

The receipts

Real systems. Real numbers.

Every figure here comes from delivered work, and each one links to the job behind it.

945

clear facts pulled from three and a half years of email, each one traceable to the message it came from.

Case 01 · Landscaping →
33→120+

contacts in a customer list, rebuilt from the owner’s own email history.

Case 01 · Landscaping →
12.4M

words read and turned into 26 operational growth playbooks, audited against the source.

Case 02 · Playbooks →
22×

the runtime, for a worse result. That’s why we test cheaper options before choosing a model.

How we control cost →

How we work

Checking isn’t an extra. It’s how the work gets built.

AI that touches your customers, your money or your reputation has to be right, not just impressive in a demo.

01

A person approves what goes out

Systems that act for you find, score and draft. You approve before anything leaves the building.

02

Nothing checks its own work

A second pass reviews the first without seeing its conclusions. Flags are re-tested by separate reviewers.

03

You’ll get a negative answer if that’s the answer

One validation programme we ran came back “don’t build it.” That recommendation was accepted.

04

You pay for the result, not the fanciest model

We test the options against the actual job, including cheaper ones, and measure exactly what’s lost.

05

Your data stays yours

Systems run on credentials you issue and can switch off. Your data is never sold, shared or used to train anything.

06

We name the failure modes first

Before a job starts, we list the ways it could fail and build the check for each one into the process.

How we verify

Talk to us

Something here sound like your business? Start with a short call.

No slide deck and no hard sell. If AI isn’t the right tool for your problem, you’ll hear that on the call.

  • What you’re trying to fix
  • Whether AI is genuinely the right tool for it
  • What it would take

Where would AI pay in your business?A short first call. Straight answers.

Book a call