Automation Consultant for Hire
I automate the work your team repeats, and I tell you first whether the numbers justify building it at all.
133 completed contracts, 106 five-star reviews and a 100% Job Success Score on Upwork. 71% of that work came from clients who hired me again.
Where these projects go wrong
Automation projects fail at scoping, not at coding. Nobody put a number on the problem, so a workflow gets built that saves four minutes a week and costs a fortnight to maintain.
The second failure is quieter. The automation runs, an API returns an error nobody watches, and for three weeks records silently do not sync. Retries, idempotency and alerting are the difference between an automation and a liability.
What I build
Lead and intake routing
Enquiries captured, deduplicated, enriched and routed to the right person with the context they need, instead of sitting in a shared inbox.
CRM and system synchronisation
Records kept consistent across the tools you already pay for, with conflict rules decided up front rather than discovered later.
Document and billing workflows
Files parsed, data extracted, invoices and approvals moved along, with a human step wherever money or a customer is involved.
Rescue work
Existing n8n, Make or Zapier setups that broke, half-finished, or were left behind by whoever built them.
How the work runs
- Put a number on it firstMinutes per task times volume times loaded cost, minus the build and the maintenance. If it does not pay back inside a year I will say do not build it yet.
- Map the real pathIncluding the exceptions, because the exceptions are what break automations.
- Build with failure in mindRetries, idempotency so a replay does not double-charge anyone, and alerts that reach a person when something stops.
- Hand over the controlsYour team can see runs, rerun a failure and change the parts that change often, without calling me.
Proof
Serverless media pipelines on AWS
Queues, auto-scaling workers and retry behaviour, refined across six contracts with the same client.
OCR and document intelligence
Google Vision and Document AI extraction with field structuring on top, so the output is data rather than text.
Stack
n8n, Make, Zapier, Python, FastAPI, Node.js, PostgreSQL, Supabase, Stripe, MailerLite, HubSpot and GoHighLevel APIs, webhooks, Docker
Questions clients ask
How do I know an automation is worth building?
Hours saved, error cost and response-time value, minus build and running cost. If the payback is under six months, build it. Between six and twelve months, build the smallest version. Beyond that, fix the process manually until the volume justifies it.
n8n, Make or custom code?
n8n when you want to own and self-host the logic, Make or Zapier when speed matters more than control, custom code when the workflow has real branching or handles money. Most builds end up a mix, and I will explain which parts went where.
Can you fix an automation someone else built?
Yes, that is a common request. I start with a diagnosis of what is actually failing and what it will take to finish it, before touching anything.
What happens when an integration changes?
Alerting tells you before your customers do, and the workflow is built so a failed run can be replayed safely rather than needing manual repair.
Tell me what is broken
Send the workflow, the system or the idea. You get a straight answer on whether it is worth building, and what it would take. If I am not the right person, I will say so.