AI Automation
AI agents and automated workflows that take real work off your team.
AI voice agents that answer and qualify calls, n8n workflows that move data between your systems, and model-assisted steps that classify, summarise and route, all with human approval where it matters and full logging.
- Services
- 3
- Platforms
- OpenAI · Claude (Anthropic) · n8n · REST APIs
The challenge
Where AI automation pays off first
- Calls missed after hours or during busy periods
- Leads typed by hand from forms, calls and messages into the CRM
- Staff reading and sorting inbound emails and messages
- Follow-ups and reminders that depend on someone remembering
- Data copied between phone system, CRM, ERP and spreadsheets
Approach
Rules, AI and people, each where it fits
Rules-based automation
Fixed steps in n8n that run the same way every time: when a call is missed, text the caller, create a lead and alert the owner. Predictable and inexpensive.
AI-assisted steps
A model classifies, extracts, summarises or converses. Outputs are validated, and uncertain cases go to a person.
Human approval
Anything that changes important records, sends external messages or spends money can wait for approval. The approval point is designed in.
Logging and monitoring
Every run records what happened and why, errors alert a named owner, and costs are tracked.
Services
AI Automation services
3 services. Each can be engaged on its own or combined into a wider project.
Workflow automation
End-to-end automation of the processes that currently depend on copying, checking and chasing.
AI AutomationAI agents and model-assisted workflows that read, classify, summarise and route work across your systems, with human approval where it matters.Explore service
n8n Workflow Automationn8n workflows that connect your phone system, messaging, CRM, forms and databases, self-hosted or cloud, with error handling built in.Explore service
Conversational AI
Voice and chat agents that handle defined conversations and hand off cleanly to people.
Process
How the work proceeds
Four stages with clear decision points and acceptance criteria.
Map the workflow
The current steps, systems, owners and exceptions are mapped so automation targets real waiting and rekeying, not imagined ones.
Define boundaries
We agree what the automation does, what a person approves, what is logged and what happens when a step fails.
Build and evaluate
Workflows and agents are built in a test environment and run against representative cases, including the awkward ones.
Launch and monitor
Go-live is staged, errors are alerted, and you receive run notes, credentials ownership and a maintenance guide.
How acceptance is assessed
- Agreed test cases run end to end in the target environment.
- Approval, exception and failure paths behave as documented.
- Every run is logged without retaining unnecessary personal data.
- The operating owner has walked through the handover notes.
Technologies
Platforms used in this work
Named for experience, not partnership or certification.
FAQ
Common questions
Is AI automation reliable enough for customer calls?
For defined conversations with clear escalation, yes. Agents are tested against real scenarios and transfer to people for anything outside their scope.
Do we need to replace our systems?
No. Automation connects the phone system, CRM and tools you already use through their APIs.
Self-hosted or cloud n8n?
Self-hosting gives control and lower cost at volume; cloud removes maintenance. Both are supported.
What happens if an AI provider has an outage?
Work is queued or routed to a person, so an outage delays rather than loses it.
Next step
Plan your automation.
Describe the workflow or calls you want to automate, the systems involved and where work waits today.