AI Services
AI agents and workflow automation
Automation gives you hours back every week. We map your repetitive processes and rebuild them as reliable workflows: lead routing, follow-ups, reporting, invoicing and the glue work between your tools.
Who it is for: Teams copying data between tools, chasing follow-ups manually, or drowning in routine admin.
Everything in this service
- Process mapping and automation audit
- Workflows built in n8n, Make or Zapier
- Custom AI agents where rules are not enough
- CRM, email and e-commerce automation flows
- Documentation and failure alerts, so nothing silently breaks
What to expect
- Repetitive tasks running without a human in the loop
- Faster follow-ups, so fewer leads go cold
- A documented system, not a mystery only one person knows
How ai automation actually works
Map the process before you automate anything
Automating a process you have not mapped means automating whatever it currently is, including the parts that exist because someone left three years ago and nobody questioned it since. The mapping step is where most of the value in an automation project is created, and it is the step people want to skip.
A useful map records the trigger that starts the process, every step in order, who performs each one, what system holds the data at each point, the decisions that get made and the rules behind them, and the exceptions. Exceptions are the important part. Almost every real process has a happy path that runs most of the time and a set of awkward cases that the person doing it handles by judgment. If you automate only the happy path and do not decide what happens to the rest, the exceptions do not disappear. They pile up somewhere quieter.
The map almost always reveals steps that should be deleted rather than automated. Duplicate data entry because two systems were never connected. A report nobody reads. An approval added after one incident and never reviewed. Removing a step is faster, cheaper and more reliable than automating it, and a good automation audit produces a delete list alongside the build list.
- Record trigger, steps, owners, systems, decisions and exceptions
- Map the awkward cases, not just the happy path
- Look for steps to delete before steps to automate
- Watch for work that exists only because two tools do not talk
- Get the map confirmed by the person who actually does the work
Choosing what not to automate
Some work should stay human, and saying so is part of the job. The tests we apply are practical. How often does this run? A task performed twice a year rarely repays the build and maintenance cost. How stable are the rules? A process that changes every quarter will need rebuilding every quarter. How expensive is a mistake? Automating a step where an error costs a customer relationship or a compliance problem needs far more care, and sometimes the answer is to automate the preparation and leave the final action to a person.
Judgment is the clearest boundary. Deciding whether to make an exception for a good customer, how to word a reply to a complaint, or whether an unusual order is genuine are not rule-following tasks dressed up as hard ones. They are actual judgment, and automating them produces confident bad decisions at speed.
The most useful pattern for these cases is assisted rather than autonomous. The system gathers the information, drafts the output, flags what looks unusual and presents it to a person who approves, edits or rejects. You keep most of the time saving and none of the risk. It is also a sensible first stage for anything you intend to fully automate later, because the approval queue shows you exactly how often the system would have been wrong.
- Frequency, rule stability and cost of error decide the case
- Rare tasks rarely repay build plus maintenance
- Keep genuine judgment with people
- Use draft-and-approve where the stakes are high
- Run assisted for a while before going fully autonomous
Error handling: what happens when a step fails
Automations fail. An interface changes, a service has an outage, a rate limit is hit, a file arrives in an unexpected format, a required field is empty. The question is never whether a workflow will fail but whether you will know when it does. The silent failure is the expensive one: leads that stopped syncing in March and were noticed in June.
Every workflow we build gets three things. Retries with a growing delay, because a large share of failures are temporary and resolve themselves within minutes. Alerts to a channel a human actually watches, naming the workflow, the record and the error rather than a generic message. And a defined position for anything that could not be processed, so failed items sit in one place waiting for attention instead of vanishing.
Two properties are worth insisting on. Failures should be safe to retry without doing the same thing twice, so a customer does not receive four copies of the same email because a later step failed. And a workflow should never partially complete a chain of updates and leave your systems disagreeing about the truth. Getting this right is the difference between automation that people trust and automation they quietly work around.
- Retry with growing delays, most failures are temporary
- Alert to a channel someone watches, with useful detail
- Hold failed items somewhere visible rather than dropping them
- Make retries safe so nothing gets sent or created twice
- Avoid half-finished updates that leave systems disagreeing
Credentials, access and the risk nobody budgets for
Automation platforms sit in the middle of your business with keys to everything: your CRM, your email, your accounting system, your file storage. That concentration is what makes them useful and also what makes them worth thinking about carefully.
Sensible practice is unremarkable and often skipped. Connect using accounts created for the automation rather than a staff member, so a departure does not break the workflows and so the audit trail names the system rather than a person who was not involved. Grant the narrowest permission that works, since a workflow that reads orders does not need the ability to delete them. Keep credentials in the platform vault rather than typed into a step where anyone with access can read them. Review who can edit workflows, because edit access is effectively access to every connected system. And rotate keys when someone leaves.
It is also worth knowing where data travels. A workflow that sends customer records through three services has put that data in three places, each with its own terms and its own retention. That is a question to answer before the build, not after. We document what flows where so you can check it against your own obligations, and we would point you to your own advisers on anything that turns into a legal question.
- Use dedicated service accounts, not a staff member login
- Grant the minimum permissions the workflow needs
- Store credentials in the platform vault, never inside a step
- Restrict who can edit workflows, editing equals access
- Document where customer data travels before you build
Documentation, or how to avoid a black box
The common failure of automation projects is not technical. It is that a year later, one person understands the system and everyone else is afraid to touch it. When that person is unavailable, the business either works around the automation or stops trusting it.
Useful documentation is short and answers the questions people actually have. What does this workflow do, in plain language. What starts it. What it touches. What it deliberately does not handle. What to check first when it fails. Who owns it. A page per workflow is usually enough, and it is worth far more than a diagram nobody can read.
The workflows themselves should be readable too. Steps named for what they do rather than left with default labels, notes on any step that exists for a non-obvious reason, and a change log so somebody can tell what was altered and when. We hand over the documentation with the build, and we would rather you were able to make small changes yourself than dependent on us for every adjustment.
- One short page per workflow, in plain language
- Record what it deliberately does not handle
- Name every step for what it does
- Keep a change log so surprises can be traced
- Name an owner inside your business, not only your supplier
Why every automation needs ongoing support
Automations are not finished when they go live. They sit on top of other systems, and those systems change without asking. A tool releases a new version of its interface. A form gains a field. A pricing tier changes what an account is allowed to do. A team renames a stage in the CRM and three workflows that referenced the old name stop matching anything.
Your own business changes too, usually faster. A new service, a new territory, a different approval step, a new person in a role the workflow assumed. Each of those makes some part of the original map inaccurate, and a workflow built against an inaccurate map produces work someone has to undo.
The support model that works is small and regular. A monthly look at failure logs and volumes, so a rising error rate is caught before it becomes an incident. A check that the workflows still match how the process actually runs. Adjustments as tools change. And a short conversation about what has changed in the business, which is usually where the next automation comes from. Automation without maintenance is a system that decays quietly while everyone assumes it is fine.
- Connected tools change without warning, workflows break silently
- Business changes make the original process map inaccurate
- Review failure logs and volumes monthly
- Re-check that workflows still match reality, not just that they run
- Budget for maintenance at build time, not after the first failure
Where to start, and what a first project looks like
The best first automation is boring, frequent and low-risk. Something that happens many times a week, follows clear rules, and costs little if it needs correcting. Data moving between two tools, an internal notification, a follow-up that currently depends on someone remembering. It proves the approach, builds confidence, and gives your team a real sense of how the system behaves before anything important depends on it.
The projects that go badly are usually the ambitious ones chosen first: a full lead-to-invoice chain rebuilt in one pass, touching six systems, with nobody yet sure whether the mapped process matches the real one. Sequence matters. Get two small workflows running reliably, learn from what they surface, and then take on the process that spans departments.
Measure the result in time and in errors rather than in workflow count. Hours returned to the team each week, follow-ups that now happen on time, records that no longer get retyped and mistyped. Those are the numbers that justify the next build, and they are the ones we report on.
- Start with frequent, rule-based, low-consequence work
- Prove two small workflows before attempting a cross-department process
- Measure hours returned and errors removed, not workflows built
- Let the first builds correct your understanding of the process
- Expand scope only once reliability is demonstrated
A clear path, step by step
- 01
Audit and plan
We check the current state, find what is holding you back, and agree a prioritised plan.
- 02
Fix and build
We make the changes: technical fixes, content, structure and internal links.
- 03
Make it citable
We add the structure and signals that help search and AI engines trust and quote the page.
- 04
Track and improve
We measure rankings, visibility and enquiries each month, then refine.
Why choose us for this
We automate the process, not just the task
Reliability engineering: alerts, retries, documentation
Honest about what should stay human
Common questions
What can actually be automated?
Anything repetitive with clear rules: lead capture and routing, data sync between tools, report generation, review requests, invoice chasing, onboarding sequences. We audit your week and show you the list.
What if an automation breaks?
Every workflow we build includes failure alerts and retry logic, plus documentation. You know within minutes if something stops, not weeks later.
Explore related work
Want this for your business?
Book a free visibility call and I will tell you honestly whether I can help.
How this is delivered
One person leads every project. Where a job genuinely needs a specialist, I bring in people I have worked with before and manage them, so you get one point of contact and one invoice rather than three suppliers blaming each other.
- You talk to the person responsible for the work, not an account manager
- Specialists are briefed and managed by me, and their work is checked before it reaches you
- One contract, one invoice, one place to chase