Automation & Workflows
Not every process needs an agent. Most of the work in a business process is moving data from one place to another, checking it and telling someone when something happens. I build that automation for the processes no off-the-shelf tool covers: deterministic where it can be, with an AI step only where it needs judgement.
Capabilities in this area
The workflows and pipelines that do the work, and the dashboards and alerts that show it is being done.
Workflow Automation
End-to-end automated processes on n8n, custom scripts and orchestration platforms: trigger-based workflows, multi-step orchestration, error handling and retries.
Workflow automation → CC-SVC-02Data Pipelines
Flows that ingest, clean, enrich and route information, from scheduled API polling and ETL jobs to event streams and webhooks.
Data pipelines → CC-SVC-06Dashboards & Reporting
Views of pipeline results, agent outputs and system status, built for the people who make decisions from them.
Dashboards & reporting → CC-SVC-08Notification Systems
Alerts through email or Slack when jobs finish, detect anomalies or need a person to decide.
Notification systems →Where automation ends and agentic AI begins
The two overlap, and most projects use some of each. The difference is who decides the next step.
In an automated workflow, the steps are fixed: when this happens, do that. A model might classify an email or extract a field along the way, but the workflow decides what happens next. That makes it predictable, cheap to run and easy to audit, and it is the right design for most repetitive work.
In an agentic system, the model chooses which tools to call and in what order. That handles open-ended tasks a fixed workflow can't, at the cost of more testing and oversight. I start with the simplest design that does the job, and add an agent only where the task needs one.
Where an AI step runs on every record, such as routing tickets or tagging documents, a trained classifier is often cheaper and more consistent than calling a general model each time.
Working with me on an automation
Deterministic automation for the processes no off-the-shelf tool covers, with an AI step (or a small trained model) only where a decision needs judgement.
Who it's for
- Teams copying data between systems by hand
- Processes that run on spreadsheets and reminders
- Operations that need a report or an alert nobody currently produces
- Teams with fragile automations that break silently
What you get
- Working workflows, pipelines, dashboards or alerts
- Error handling, retries and monitoring
- Documentation your team can maintain from
- Hosting on your infrastructure or n8n
- All code and configuration, yours
What I need from you
- A walk-through of the process as it runs today
- Access to the systems involved
- Who should be told when something fails
- A process owner
How it runs
Typically 2–6 weeks for a single process.
- Week 1
Map the process
Steps, systems, data and failure points.
- Week 1–2
Design
What runs where, what triggers it, where people review.
- Weeks 2–5
Build and test
Build against real data and edge cases.
- Weeks 4–6
Run and hand over
Monitored rollout and handover.
Single workflows and data pipelines start around $8,000. Larger automation programmes are quoted on scope after a short call.