AI automation agency UK

AI automation agency for UK SMEs

We automate the repetitive work that slows teams down — but only after the workflow, data access, and failure modes are understood.

Average first slice
Two to four weeks
Stack posture
We integrate; we do not replatform
Failure modes
Designed for, rehearsed, monitored
Ownership
Yours from week one

Good fit when

For teams with one workflow worth automating, not a vague AI mandate.

The strongest first projects are usually specific, visible, and boring: the inbox, CRM, document, or ticket flow everyone already knows is costing time.

Current situation

A real process is slow or fragile

You can already name the manual step, the system it touches, and the team carrying the work.

What we help with

Workflow automation around your existing stack

We look for repeatable work with clear inputs, clear outputs, and a safe review point.

Common concern

Will this break when it meets production?

The build path includes logs, accuracy checks, a quiet trial run alongside your team, escalation, and human review where it matters.

First stepScope one workflowBring the candidate workflow. We will test whether it should be automated, redesigned, or left alone.

Three real-shape automations

Specific workflows we have shipped or could ship next.

Each one starts with the actual document, ticket, or email the team is touching today. Not a generic "automate your business" pitch.

Mortgage broker · 25 people

Document-to-CRM intake without re-keying

New-client packs arrive as PDFs, scanned IDs, and bank statements over email. Brokers were spending the first 40 minutes of every case re-typing it into the CRM and the lender portal.

What we'd ship

An intake pipeline that classifies inbound attachments, extracts the structured fields the CRM needs, flags anything ambiguous for a human, and produces a clean case record ready for the lender. The broker reviews, approves, and submits — no re-keying.

Timeline·Three weeks to first live case, four weeks to full rollout
B2B SaaS · 40 people

Support triage that routes before the human sees it

A growing SaaS team was drowning in a shared inbox. Tier-1 questions, billing tickets, and outage reports all looked the same on arrival. SLAs were slipping.

What we'd ship

A triage agent that reads inbound support email, drafts the answer for tier-1 patterns from the approved KB, routes billing to finance, and escalates anything matching outage or churn signals. Humans review the draft before it sends.

Timeline·Four weeks end-to-end, including a two-week trial run
Consultancy · 30 people

Inbox-to-task automation that respects judgment

Partners were buried under client emails. Important commitments were getting buried alongside calendar invites and CC noise. Project leads found out about new asks days late.

What we'd ship

An inbox watcher that identifies commitments, deadlines, and asks across nominated mailboxes, drafts a task in the project tool with the right owner and due date, and asks the partner to confirm. No silent task creation, no missed asks.

Timeline·Two weeks pilot, two weeks rollout to leadership

How the build runs

Trace the work. Automate the repeatable. Govern the rest.

We refuse to automate a workflow we have not watched a human run. The cost of getting that wrong is paid in customer trust.

  1. Step 01Trace the work from request to outcome

    We sit with the people running the workflow. We map happy path, exceptions, handoffs, and the places where the current process quietly papers over data quality.

  2. Step 02Separate rules, judgment, and exceptions

    Rules become deterministic code. Judgment becomes a tightly-scoped model call with grounding. Exceptions get a named human owner and a clear handoff.

  3. Step 03Build the integration path around your stack

    We integrate with what is already running — CRM, inbox, document store, ticketing, finance. We do not push a replatform unless your stack is the bottleneck.

  4. Step 04Monitor before expanding scope

    Every automation ships with logs, accuracy checks, and alerting. We run it quietly alongside the current process first, then live, then expand. No silent quality drift.

Who this is for

Operators with a specific bottleneck — not a generic AI mandate.

COO with CRM hygiene pain

Your CRM is the source of truth on paper. In practice, it is half-full, contradicts the spreadsheet, and the team has stopped trusting the pipeline number.

  • A pipeline review that takes three days every month
  • Sales ops asking for another hire
  • Reports that nobody quite believes

Head of ops with document load

PDFs, scans, and structured forms arrive faster than the team can process them. Re-keying is the actual job.

  • Backlog measured in days
  • Errors that surface downstream
  • Limited budget for headcount

Support lead with SLA pressure

Inbound volume is rising and the team is missing first-response SLAs. Hiring is slow and the wrong answer.

  • Tier-1 patterns repeating daily
  • A KB that is mostly correct, mostly
  • A board asking why CSAT is drifting

Common questions

How it behaves once real work hits it.

Which tools do you typically automate against?

We work around whatever already runs the business: CRMs (HubSpot, Salesforce, Bullhorn, Pipedrive), inboxes, document stores, finance systems, ticketing tools, and bespoke internal systems. We integrate; we do not insist on a platform swap.

Do you replace staff?

No. We target the repetitive, error-prone, or delayed parts of a workflow so your team focuses on judgment, relationships, and exceptions. Headcount conversations are not our pitch.

How do you keep automations reliable in production?

Narrow scope, logs, accuracy checks, alerting, and a clearly defined human escalation path before we expand capability. Reliability work is part of the build, not an afterthought.

What happens when the automation gets something wrong?

Exceptions are designed for. Every workflow has a defined human-in-the-loop path, an audit trail, and a rollback. We rehearse failure modes before going live.

How long until something is in production?

A first automation slice typically takes two to four weeks once data access is sorted. We deliberately keep the first slice small so it can be inspected, measured, and trusted before expansion.

How do you price ongoing maintenance?

A light monthly support arrangement covers monitoring, accuracy checks, and minor adjustments. Larger expansions are scoped as fresh work so you can see what you are paying for.

Start small, prove it, expand

Pick one workflow. We will tell you whether it is worth automating.

If the workflow is the wrong candidate, we will say so. The fastest way to lose trust is to automate something that should be redesigned instead.