[ 00 // AUTOMATION EXAMPLES ]
Small tasks. Hours back, every week.
I analyse how your team actually works, find the routine tasks eating their day, and build custom AI apps that do those tasks — shipped with tests and approval gates.
[ 01 // EXAMPLES BY DEPARTMENT ]
What gets automated
Six departments, eighteen tasks teams still do by hand — each one a scoped, buildable automation project.
Finance & Admin
Invoices, expenses, and reports — with no retyping.
Invoice data entry
The AI reads PDF and email invoices, extracts the fields, matches them to purchase orders, and books a draft entry in your accounting tool for one-click approval.
Saves roughly 30–60 minutes of typing per bookkeeper per day and removes the typos that come with manual entry.
Expense categorization
Employees photograph receipts on their phone; the AI reads them, categorizes each expense against your chart of accounts, and flags policy outliers for review.
The monthly expense close drops from days to hours, with every outlier caught before it reaches the ledger.
Payment reminders
The AI drafts polite, escalating payment reminders straight from your ledger — you review and approve before anything is sent.
Invoices get paid faster without anyone chasing them by hand.
Sales
More selling, less copy-paste into the CRM.
Lead research & enrichment
Before every call, the AI researches the company and contact and writes a short briefing — recent news, role, likely pain points — directly into the CRM.
Reps save around 5 hours a week of manual research and walk into calls prepared.
CRM updates from email
After each customer email or call, the AI drafts the CRM log entry and the next step; a rep approves it with one click.
The CRM stays current without end-of-day admin, so forecasts rest on real data.
Quote & proposal drafting
The AI drafts quotes and proposals from your price list and past winning proposals, ready for a human to check and send.
Quotes go out the same day instead of sitting in a draft folder for a week.
Customer Support
Faster answers without hiring more people.
Ticket triage
The AI categorizes, prioritizes, and routes incoming tickets, and drafts first replies to common questions for an agent to approve.
First response time drops from hours to minutes, and urgent issues surface immediately.
Conversation summaries
Long email threads and chat histories are compressed into a three-bullet summary with the customer request highlighted.
Handovers and escalations stop losing context between agents.
FAQ assistant
A website widget answers the repetitive questions from your own docs; anything it cannot answer confidently passes straight to a human.
Roughly a third of routine tickets are deflected, and the ones that remain get full attention.
Operations
Reports and alerts that write themselves.
Weekly KPI reports
The AI pulls the numbers from your systems every week, writes the digest in your format, and flags anomalies worth a look.
Saves the Friday report grind — around 3 hours a week — and surfaces problems before the month-end review.
Order & inventory alerts
The automation watches stock and order flow and warns you before a stockout or overselling happens, not after.
Fewer emergency purchases and fewer apologies to customers.
Meeting notes → action items
Recordings and notes from meetings become assigned, dated tasks in your tracker, ready for a quick human check.
Nothing agreed in a meeting gets lost between the call and Monday.
HR & Hiring
Screening minus the paperwork.
CV screening summaries
Every applicant is summarized against your must-have criteria as a comparable scorecard, so a human makes the decision with far less reading.
Screen 50 applicants in the time it used to take to read 10.
Job description drafts
Give the AI a few bullets about the role and it drafts a job ad in your tone, structured and ready for posting.
A ready-to-review posting in about 10 minutes instead of an afternoon.
Onboarding checklists
New hires receive a personalized, per-role onboarding plan automatically — accounts, documents, first-week schedule.
Consistent first weeks for every hire, with zero manual coordination.
Documents & Data Entry
PDF chaos turned into clean data.
PDF → spreadsheet/ERP extraction
Contracts, delivery notes, and forms are read and their fields typed straight into your spreadsheet or ERP — where they belong, checked by a human.
Document backlogs get processed overnight instead of over weeks.
Email sorting & drafting
The routine inbox is triaged automatically — orders, invoices, and questions routed where they belong — and standard replies are drafted for approval.
Inbox time is roughly halved, and nothing sits unread for days.
Document classification & filing
Incoming documents are recognized, named consistently, and filed to the right folder or case automatically.
An audit-ready archive without the filing hours.
[ 02 // HOW IT WORKS ]
How the audit works
A fixed, four-step engagement — from a raw task list to automations running in production.
[ 01 ]
Audit
I sit with your team, map daily routines, and measure where the hours actually go.
[ 02 ]
Identify
You get a shortlist of automation candidates ranked by hours saved versus build effort, each with a fixed price.
[ 03 ]
Build
I build the custom app or agent, integrate your tools, and ship it with tests, approval gates, and monitoring.
[ 04 ]
Maintain
Models and APIs change; I keep the automation running and improve it as your process evolves.
[ 03 // QUESTIONS OWNERS ASK ]
Frequently asked questions
How does the free task audit work?
A short call plus a look at one or two of your daily routines. You receive a prioritised list of automation candidates with effort and impact estimates. No commitment.
Do you need access to our data?
Not for the audit, which is about process rather than data. Builds use least-privilege access, GDPR-aware design, and can run entirely on EU infrastructure.
What does a typical automation cost?
Small automations are fixed-price, scoped after the audit. The price depends mainly on how many tools must be integrated — the fewer the integrations, the lower the cost.
What if the AI makes a mistake?
Automations are built human-in-the-loop: the AI drafts, a human approves. Critical flows get golden-dataset tests and monitoring before anything touches production.