An AI automation agency for work that has to run every day.
As an AI automation agency we get hired for one reason: recurring manual work that scales with headcount instead of revenue. Triage, reconciliation, data moved between two systems that will never be replaced. We automate it deterministically where we can and with models only where we must, because the cheapest automation is the one that cannot hallucinate.
The pitch most AI automation companies make is that a model can do the whole job. It usually cannot, and the projects that survive contact with production are the ones that used a model for the narrow part it is genuinely good at — reading unstructured text, classifying a messy input, drafting a response — and ordinary deterministic code for everything else. A workflow where the model decides what happens next is a workflow nobody can debug at 2am.
So our AI automation services are built the boring way: an explicit flow with named steps, typed inputs and outputs, retries and dead-letter handling, an audit trail of every decision, and a human approval gate wherever the cost of being wrong is real. Where a model sits inside a step, it is constrained, evaluated against a golden set, and monitored for drift like any other dependency.
The work is usually AI workflow automation across systems rather than inside one — your ERP, PIM, helpdesk, storefront and spreadsheets, none of which are going away. That is the same integration problem we have solved without models for two decades: SAP-backed pricing, stock and fulfilment logic across MASCOT Workwear's 20+ markets and TTI's 18 regional sites, 13 country sites for Goodiebox. On Endota Spa the automated piece was the customer-service workflow behind the booking platform.
We build on n8n where a visual, self-hostable orchestrator is the right answer, and in application code where it is not. n8n automation is genuinely good for the connective tissue and genuinely bad as a place to hide business logic, and we will tell you which side of that line your process falls on. Self-hosting keeps your data and your workflow definitions on infrastructure you control.
Where the process is commerce-specific — returns triage, fraud screening, supplier reconciliation inside the store — e-commerce automation is the better-scoped page. This one is for business process automation and AI across the rest of the company.
Workflow automation services, in the shapes they usually arrive in.
Document and message triage
Inbound email, PDFs, invoices, supplier forms and tickets read, classified, extracted and routed. The highest-value place to put a model, because the input is genuinely unstructured.
Reconciliation between systems
Orders against payments, stock against the ERP, catalogue against the PIM. Exceptions surfaced as a queue a human can clear, rather than a report nobody opens.
Data entry and system-to-system flow
The work someone currently does by copying between two tabs. Typed, idempotent, retried, logged — and monitored so a silent failure is impossible.
Drafting with a human gate
Replies, descriptions, summaries and internal notes drafted by a model and approved by a person. Approval rate becomes the quality metric, and it is visible from day one.
Self-hosted orchestration
n8n on your own infrastructure — Docker, Kubernetes or a single Ubuntu host — with workflow definitions in version control and secrets outside them. No per-task pricing on a vendor's meter.
Evaluation harness before feature
A golden set built from your own queries and records, scored automatically on every change and wired into CI as a release gate. It is what makes every later claim checkable — including ours.
How an automation gets built here.
Measure the current process
Volume, handling time, error rate and who does it now. If we cannot measure it before, no claim about after means anything.
Split deterministic from model work
Explicitly, on a diagram, before any code. Most steps turn out not to need a model, which is what makes the result cheap to run and possible to debug.
Ship one flow to production
Narrow and real, with a human gate and full logging, running alongside the manual process rather than replacing it on day one.
Remove the gate on evidence
Automation is widened only where the approval data says it is safe. Some gates stay forever, on purpose.
The commercial shape, without a discovery call.
We quote a target cost per interaction and a target volume of work removed before the build, then report against it. We do not publish percentage uplifts from other clients as a forecast for yours — the ones you see on agency sites are rarely comparable and never checkable.
The stack.
Common questions.
What makes you different from the other AI automation agencies?
Mainly that we will argue against using a model. Most of what gets sold as AI automation is a queue, a schema and some error handling with a model bolted on, and it is more reliable and far cheaper when built that way deliberately. The other difference is that we are an AI automation company that ran production commerce integrations for twenty years first, so the failure modes of system-to-system work are not new to us.
Do you use n8n, or write code?
Both, chosen per job. n8n automation is excellent for connective tissue — triggers, connectors, orchestration you want to be able to see — and poor as a home for business logic, which belongs in tested code. A common split is n8n orchestrating steps that call our own services. We self-host it so your data and definitions stay yours.
How do you price business process automation with AI?
Per workflow, after we have measured the current process. We quote a target cost per interaction and a target volume of work removed before the build, then report against it. We do not publish percentage uplifts from other clients as a forecast for yours — the ones you see on agency sites are rarely comparable and never checkable.
What if the model gets it wrong?
Assume it will, and design for it. Every flow has a confidence path: below threshold it goes to a human, and above it there is still an audit trail and a reversal route. For anything touching money, stock or a customer promise, the human gate is the default and stays until the data earns its removal.
Can you automate a process that spans our ERP and our store?
That is the most common request, and it is our home ground. We run SAP-backed pricing, stock and fulfilment logic across MASCOT's 20+ markets and TTI's 18 regional sites. The boundary design — who owns the truth, what happens when one side is down — matters far more than the model choice. See ERP integration.
Is this the same as your e-commerce automation service?
Overlapping but scoped differently. E-commerce automation covers operational work inside the store — returns triage, fraud screening, supplier reconciliation — as a defined service. This page covers automation across the wider business. If your process is entirely inside the storefront, start there.
Where to next.
Name the process that eats the most time.
Tell us the volume and who handles it now. We will come back with what can be automated deterministically, what genuinely needs a model, and what should stay manual.