AI

AI applied where it removes work.

For teams being sold agents and copilots without a straight answer on what changes. We start inside the work, find where the same judgement is repeated, and automate only that. with a person still accountable.

  • Ops-heavy teams
  • High-volume intake
  • Support & sales desks
AI & Software: Custom AI, AI Consulting, AI Integrations.

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What an AI engagement actually changesExample — inbound desk
Reading and sorting inboundTwo people, all morningSorted on arrival
Answering the known questionsCopy-pasted, inconsistentDrafted, cited, approved
Finding the relevant historySearch across four toolsRetrieved with sources
Deciding what happens nextA person decidesStill a person decides

The last row is the point. We automate the reading, the retrieval and the drafting — the consequential decision keeps a human on it, with an approval step and a record of what the system did.

What’s included

Six things, every AI engagement.

Named plainly, paired with what it actually means. No model demos, no pilot that never leaves the sandbox.

01

Opportunity audit

Two weeks inside the actual work, watching what people repeat. You get a ranked list of what is worth automating — and what is not.

02

Retrieval over your own data

Answers grounded in your documents, inventory and history, with the source attached to every claim so it can be checked.

03

Intake & triage agents

Inbound read, summarised, categorised and prioritised before a person opens it, in the tools your team already works in.

04

Human in the loop

Anything with consequences gets an approval step by default. The system proposes; a named person decides.

05

Evaluation & guardrails

A test set built from your real cases, so we can prove a change made things better before it goes near a customer.

06

Audit trail & review

Every input, source and action on the record, so you can answer what the system did and why, months later.

Your starting point

Know where you stand.
See what needs attention.

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How it goes

Three steps, and you see each one.

The audit is a real deliverable. If nothing here is worth building, that is a valid outcome and we say so.

01

Audit the work

We sit with the team doing the task, count the volume, and separate the parts that are genuinely repetitive from the parts that need judgement.

Deliverable — ranked opportunities
02

Build the narrow thing

One workflow, scoped small enough to evaluate honestly, running on your data with a human approving the output.

Deliverable — one live workflow
03

Measure, then widen

We compare against the test set and the hours it was meant to save. It widens only once the numbers hold.

Deliverable — evaluation & next scope

Related industries

Where we’ve done this before.

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Bring us the task, not the tool.

Tell us the work you want off your team. We will tell you whether AI is the honest answer for it.

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