Small Automation Examples
Start with the part that’s annoying you the most.
If you’re re-entering information, chasing approvals, or losing track of requests, a small automation can fix one workflow quickly. Click a tile to see the workflow, the tools it connects to, and the guardrails.
Stop retyping the same details into multiple systems.
Fewer errors
Cleaner data
Fewer handoffs
Generate quotes, letters, or documents from stored data so they’re consistent and don’t need to be rebuilt each time.
Use AI to read incoming invoices, extract key details, and send them for approval before they reach accounting.
Log time by voice or text at the end of each day instead of chasing time sheets later.
Reply fast, capture the lead, and create the follow-up task automatically.
Faster response
No leads lost
Consistent follow-up
Sort incoming emails and PDFs and route them to the right person with the next steps.
Clear ownership
Less chaos
Nothing missed
Answer common questions 24/7 and capture qualified enquiries with context.
24/7 answers
Better leads
Less back and forth
A short summary plus alerts when something needs attention
Visibility
Early warnings
Consistent reporting
These starter automations work well on their own and they also create the building blocks for bigger improvements later.
If you’re not sure where to start, a quick review of your current workflow usually makes the next step obvious
AI & Automation Strategy
A practical strategy service designed to help businesses understand where automation and AI will have the biggest impact and how to move forward with confidence.
What this service is
This service is designed for businesses that know automation is needed but want clarity on what to automate first, why it matters, and how it will be implemented.
We don’t deliver abstract reports. We create a practical automation roadmap that leads directly into build and deployment.
What we do
We work with you to:
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Identify high impact automation opportunities across operations, finance, and reporting
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Map real workflows (not idealised processes)
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Assess where AI can reduce manual effort, errors, and delays
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Prioritise automation based on effort vs return
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Define an implementation plan that fits your systems and team
What you get
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A clear automation roadmap with prioritised use cases
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Defined workflows ready for build
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Tool recommendations aligned to your environment
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Estimated implementation effort and sequencing
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A clear path into automation implementation (no re-work)
Who this is for
This service is suited to small and medium businesses (SMBs) that:
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Have grown beyond manual processes and spreadsheets
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Are unsure where AI fits practically
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Want to invest in automation with confidence
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Need clarity before committing to implementation
How this leads to implementation
Everything produced in this phase is build-ready.
Most clients move directly into:
Workflow & AI Automation Implementation
No duplicated work. No re-analysis.
Example of a Complete Business Flow
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Designing a full business flow starts with a simple question:
Where does information first enter the business?
Most systems only see information after it has already been typed into them. By that point, you’re locked into their structure, their reports, and their limitations.
The strategy behind this flow I built is to capture information before that happens, structure it once, and then let it move through the business without being re-entered.
In the flow you’ve seen on this site, information enters naturally:
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a message in Teams
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an invoice arriving by email
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time logged at the end of the day
At that moment, the information is captured and stored centrally as structured data. This becomes the single source of truth for the rest of the process.
From there, each step builds logically on the last.
When a quote is created and accepted, it doesn’t just send a document. It establishes the foundation for the work:
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the client is confirmed
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a project number is created
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folders and records are set up automatically
That project then becomes the anchor point for everything that follows.
As work is done, time is logged against the project.
As costs arrive, invoices are read, approved, and linked to the same project.
Nothing is floating around unconnected.
Because approvals happen early, the data stays clean.
Because the data is structured, analytics can run continuously.
This is where Business Intelligence changes role.
Instead of being something you look at once a month, the BI dashboard updates every time something happens:
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a quote is accepted
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an invoice is approved
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time is logged
That means the numbers you see are always current, without running reports or reconciling systems. View any business analytics you need set up on your dashboard.
Only once the information is complete and approved does it flow into accounting.
Accounting becomes the place where outcomes are recorded not where the business process lives and not where you try to reconstruct what happened.
That sequencing is deliberate.
It’s what allows:
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live analytics
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fewer errors
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no double entry
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and decisions based on what’s happening now, not last month
