AI Automation

Our Automation Process

This is where we listen. We’ll meet with your stakeholders, subject-matter experts, and users to fully understand:

Your current workflows—what works, what doesn’t, bottlenecks, redundant tasks.
Where data lives, which systems are in play, integration possibilities and constraints.
Business goals: what automation success looks like for **you** (speed, cost saving, error reduction, scale etc).
Any compliance, security, or governance requirements you need satisfied.

Deliverables: Automation opportunity map; recommended toolset & platforms (including n8n, where relevant); initial ROI and timeline estimate.

With clarity on scope, we move into designing how the automation will actually work. This includes:

Workflow mapping: defining each step of the process, decision points, triggers, actions & fallbacks.
Systems & integration design: how your platforms (CRMs, databases, APIs, third-party apps) will talk to each other.
Data design: inputs, outputs, transformation rules, error handling, and monitoring.
User experience (UX) and human interactions: what parts remain manual (if any), how hand-offs occur, notifications, alerts etc.

Deliverables: Process flow diagrams; technical spec; UX mockups for any interfaces; integration plan; security & governance plan.

In this phase, we firm everything up to ensure alignment and reduce risk before building:

Finalise requirements: confirm all workflow steps, data sources, edge cases, error paths.
Prototype / Proof of Concept (PoC) where needed—for complex triggers, key integrations, or AI components.
Validation with stakeholders & end-users: review, feedback cycles, iterate until all are on board.
Define success metrics & KPIs: time saved, error reduction, throughput, cost, adoption etc.

Deliverables: Validated spec document; any prototypes; KPI / metric sheet; approved sign-off to move to delivery.

This is where ideas become reality. We build, test, deploy and support your automation:

Implementation: building workflows (e.g. using n8n), setting up integrations, coding as needed, configuring triggers and actions.
Testing & QA: unit tests, integration tests, edge case testing, user acceptance testing (UAT).
Deployment: moving to production/ live environment, ensuring minimal disruption, backups, rollback planning.
Training & change management: training your team, creating documentation, support materials.
Monitoring & optimisation: post-deployment monitoring, gathering feedback, analysing metrics, refining workflow for performance and reliability.

Deliverables: Fully functional automation system; documentation & training; monitoring dashboard; ongoing support plan.