Automate

Automation you can name, measure, and switch off.

Not a platform and not a transformation programme. Three or four specific workflows that currently eat your team's week, built properly, monitored in production, with a person kept in the loop where the judgment belongs to a person.

Book an AI Workflow Assessment How we build it

Built for businesses of 10-100 people Works alongside your existing IT and vendors Fixed-scope assessment, no long-term commitment Security and governance built in, not bolted on

The question is never whether AI can do it.

It is whether a given task happens often enough, follows rules clear enough, and costs enough when it is missed to be worth building and maintaining something. Most tasks in most businesses fail at least one of those tests. A handful pass decisively, and those are the ones we are interested in.

Below are the patterns that clear the bar most often. Each is a single workflow with a defined beginning, a defined end, and an explicit point where a person takes over.

Workflows we build

AI phone reception

Calls outside business hours reach voicemail, and most callers do not leave one.

Customer

Customer calls
Automated

AI answers and qualifies
Automated

Booked or routed
Automated

Logged with a transcript
Team

Team sees it in the morning

Lead qualification and routing

Enquiries arrive across forms, email and phone, and get worked in whatever order they were noticed.

Customer

Enquiry arrives
Automated

Enriched and scored
Automated

Routed by rules
Team

Owner picks it up

Estimate and quote follow-up

The follow-up depends on someone remembering, during a week when they are already behind.

Team

Estimate sent
Automated

Sequence runs on schedule
Automated

Replies classified
Team

Warm ones escalated

Document and invoice processing

Information that is already digital gets read by a person and retyped by the same person.

Customer

Document arrives
Automated

Data extracted
Automated

Validated against rules
Automated

Written to the system
Team

Exceptions reviewed

Customer status and updates

A steady stream of 'where are we with this?' interrupts the people doing the actual work.

Customer

Customer asks for status
Automated

Assistant checks the system
Automated

Answers from real data
Team

Escalates anything unusual

Internal knowledge assistant

The answer exists in a document somebody wrote two years ago, and nobody can find it.

Team

Employee asks a question
Automated

Assistant searches your documents
Automated

Answers with the source cited
Team

Gaps flagged for an owner

These are patterns, not a product list. What gets built for your business comes out of your assessment, in the order the roadmap ranked it.

How we approach it

Four rules that decide most of what we will and will not build.

Fix the process before you automate it.

Automating a process nobody understands does not improve it - it removes the last opportunity anyone had to notice it was wrong. If a step should be redesigned or deleted, we say so before we build.

A person stays in the loop where judgment belongs.

Every workflow has explicit checkpoints: what runs unattended, what needs approval, and what gets escalated. Irreversible actions are not left to software on its own.

Build for the exception, not the happy path.

The demo always works. The question is what happens when the input is malformed, the API is down, or the customer says something nobody anticipated. That handling is most of the real work.

It has to be monitored to be real.

An automation nobody is watching is a liability with a countdown on it. Everything we build is logged, alerted, and reviewed - which is why implementation and management are not separate offers.

How a workflow gets built

Identify

The assessment produces a ranked register. We take the top candidates - real volume, statable rules, measurable cost of failure - and confirm the numbers with the people who do the work.
Design

We map the workflow end to end, agree where a human stays in the loop, and define what happens on every exception path before anything gets built.
Pilot

It runs against real work, in parallel with the current process, with a person checking output. We tune it until the exception rate is one you would accept.
Production and monitoring

It goes live with logging, alerting and an owner. We watch it, tune it as your process changes, and tell you when a vendor change is about to break something.

Guardrails

What every workflow ships with

These are not optional extras that get added if there is budget left. They are the difference between an automation you can defend to a customer, an insurer or a prime contractor and one you quietly hope nobody asks about.

Scoped permissions

Least-privilege access to only the systems and data the workflow genuinely needs.

Human checkpoints

Named approval points before anything irreversible or customer-visible with risk attached.

Exception routing

Low-confidence and unusual cases go to a person by design, not by accident.

Full logging

What ran, what it decided, what it changed - retrievable after the fact.

Monitoring and alerting

Failures surface to us, not to your customer three weeks later.

A documented owner

Written down: what it does, who owns it, and how to turn it off.

Questions about automation

Is this going to replace our staff?

That is not how we scope it, and in businesses this size it is rarely what owners actually want. The work we take off a team is the work that is already being done badly because there is not enough time for it - the calls nobody answered, the follow-ups nobody made, the data entry that happens at 6pm. The usual outcome is that the same team absorbs more volume without more administrative headcount.

What tools and platforms do you build on?

We build on the systems you already run wherever we can - your Microsoft 365 tenant, your CRM, your scheduling and accounting systems - and add automation and AI services on top. We are not tied to a single vendor and we do not resell one. Where a new tool is genuinely needed we will say so, along with what it costs and what it locks you into.

How long before something is actually live?

The roadmap is deliberately sequenced so the first workflow reaches production inside the first 90 days rather than at the end of a long programme. Individual workflows are typically weeks, not quarters.

What happens to our data?

It is decided deliberately and written down: what each workflow can read, what it retains, what leaves your tenant and what does not. Data boundaries are part of the design, not a question we answer after go-live.

What if the AI gets something wrong?

It will, sometimes - which is why the design question is never 'is it perfect' but 'what happens when it is wrong.' Confidence thresholds route uncertain cases to a person, irreversible actions require approval, and everything is logged so an error is visible and correctable rather than silent.

Do we need to do the assessment first?

In almost every case, yes. Building the wrong workflow well is an expensive way to learn what you should have built. The assessment is what tells us which three or four are worth doing, and it is fixed-scope so it is not an open-ended commitment.

Find out what you could automate.

A 30-minute call. Tell us where the week goes, and we will tell you honestly whether there is enough here to be worth an assessment.

Book an AI Workflow Assessment