Example use cases

Where AI actually earns its keep

A working catalogue of the automations we build for small and mid-sized businesses — what the problem usually is, what gets built, and what has to stay under human control.

These are illustrative examples, not client case studies. They describe the shape of work we take on and the decisions involved. Every engagement is scoped against your own processes, systems and data.

Sales & Quoting

From enquiry to draft quote

Enquiries arrive by email, web form and phone, and someone re-types the same details into a quote template several times a day.

  • Enquiries are read and the key details extracted — product, quantity, location, deadline
  • Matched against your price list and any standing customer terms
  • A draft quote lands in the salesperson's queue for review, edit and send
  • Anything ambiguous or unusually large is flagged instead of guessed at
Human stays in control of: pricing exceptions, discounts, final send.
Finance & Admin

Supplier invoice processing

Invoices arrive as PDFs, scans and photos in half a dozen formats, and bookkeeping time is spent on data entry rather than on the numbers.

  • Documents are read regardless of layout — line items, totals, tax, dates, supplier
  • Coded against the right account using your own chart of accounts
  • Checked against the purchase order or previous invoices from that supplier
  • Anything that does not reconcile is queued for a person rather than posted
Human stays in control of: approvals, payments, anything flagged as an exception.
Customer Service

First-line support on your own content

The same forty questions arrive every week, and the answers live in manuals, spec sheets and three years of past tickets.

  • An assistant grounded strictly in your documentation and resolved tickets
  • Drafts a reply with the source it used, so an agent can verify in seconds
  • Refuses to answer outside what it can cite, instead of inventing something
  • Escalation rules for complaints, refunds, safety issues and anything legal
Human stays in control of: anything the assistant cannot cite, plus every escalation path.
Operations & Scheduling

Job scheduling and dispatch

A dispatcher rebuilds tomorrow's schedule by hand every afternoon, juggling skills, travel time and priority jobs.

  • Proposed schedules built from job requirements, technician skills and geography
  • Re-planning when a job overruns or a callout comes in
  • Customer notifications sent when a window changes
  • The dispatcher accepts, edits or overrides — the schedule is a proposal, not a decision
Human stays in control of: the final schedule and all customer commitments.
HR & Recruiting

Structured screening of applications

Two hundred applications for one role, and the shortlist gets built from whoever happened to be read first.

  • Every application summarised against the same written criteria
  • Evidence pulled out and cited, so a recruiter reviews facts rather than a score
  • Consistent structure across applicants, whatever format the CV arrived in
  • No automated rejection, and no scoring on anything outside the stated criteria
Human stays in control of: every shortlist, rejection and hiring decision. This is an area with real legal constraints — we scope it carefully.
Reporting & Compliance

Recurring reports that build themselves

Someone spends the first two days of every month assembling the same report from the same four systems.

  • Figures pulled directly from source systems rather than re-keyed
  • The commentary drafted from the movements in the numbers
  • Variances and anomalies called out rather than buried
  • Same format every month, produced the morning the data closes
Human stays in control of: sign-off, interpretation and anything going to a regulator or board.
Knowledge & Onboarding

Turning what people know into something searchable

The answer to most questions lives with two long-serving staff, and new hires take months to get productive.

  • Scattered documents, procedures and email threads pulled into one searchable place
  • Plain-language answers with a link to the source document
  • Gaps surfaced — questions people ask that nothing in the business answers
  • Access respecting who is allowed to see what
Human stays in control of: what goes into the knowledge base and who can reach it.
Marketing

Content production without losing your voice

Marketing output stops whenever the person who writes it gets busy with something else.

  • Drafts built from your own past material, so the voice stays recognisable
  • One source piece adapted to the channels you actually use
  • Claims checked against source material before anything is published
  • A review step that a person cannot skip
Human stays in control of: every claim made about your product, and everything published.
AI security

The other half of the conversation

Most AI risk in a small business is not exotic. It is ordinary staff using ordinary tools without anyone having said what is allowed.

Where your data actually goes

Which AI tools your team already uses, what they are pasting into them, whether that content is retained or used for training, and what your contracts and industry rules require.

A policy people will follow

One page in plain language: approved tools, what must never leave the business, when a human has to check the output, and who to ask. Long policies get ignored.

Securing what we build

Access controls, logging, a limit on what an automation can do by itself, and a tested way to shut it off. Every automation we deliver is reviewed this way before handover.

See one of these built end to end

We record these builds on YouTube — including the parts that do not work first time. Or tell us about your own process and we will say whether it is worth automating.