AI automation agency services
Automation in the tools you already pay for, with AI only where a human would have to think.
We automate the parts of a workflow that are wasting hours - routing, triage, data entry, document extraction, handoffs between systems - wired into the tools you already use rather than a new platform to adopt. AI goes only in the steps that need judgement; the rest is ordinary, testable code.
From $4,500 and 4 to 6 weeks for a workflow end to end. If a no-code tool would do the job, we will tell you that instead of quoting. New to working with an AI automation agency? Read what an AI automation agency actually does, or how we approach workflow automation consulting.
Who this is for
An operations, sales or support team where several people spend a meaningful slice of the week moving information between systems and making the same call over and over. Lead response, document intake, ticket triage, order exceptions, reconciliation.
What you get
- 01The workflow automated end to end, in your existing tools - your CRM, your ticketing, your warehouse, your storage.
- 02AI applied only at the judgement steps, with an evaluation set proving those steps are accurate enough to trust.
- 03Retries with backoff, a dead-letter queue, and an alert to a named human when something keeps failing.
- 04A replayable log of every run, so an argument about what happened becomes a lookup.
- 05A dashboard showing volume, failure rate and time saved - the numbers you will be asked for in three months.
- 06A manual override path, because the exception you did not model always arrives.
When n8n or Zapier is the right answer
We will say this before quoting, because a client who buys custom engineering for a problem a connector solves does not come back.
| Situation | Use n8n / Zapier / Make | Use custom engineering |
|---|---|---|
| Volume | Hundreds of runs a month | Thousands a day, where per-execution pricing bites |
| Steps | A handful, mostly linear | Branching, with state that matters across runs |
| Failure handling | A retry and an email is fine | Partial failure must not corrupt anything downstream |
| Judgement steps | One simple classification | Extraction and routing that needs evaluating and tuning |
| Testing | Nobody needs to prove it works | It touches money, customers or compliance |
| Who maintains it | Someone in operations | Your engineering team, in source control |
The honest cost comparison for self-hosting versus cloud on n8n specifically is on our n8n page, including where it stops being the right tool.
How we build it
- 01week 1
Watch the real process
We sit with the people doing it. The documented process and the actual one differ in every organisation, and the differences are where the automation would otherwise break.
- 02week 1
Split judgement from mechanics
Every step gets labelled: deterministic, or needs judgement. Only the second kind gets a model. This single decision does more for cost and reliability than any other.
- 03weeks 2-3
Build the mechanics
Integrations, state, idempotency, retries and the dead-letter queue. Unglamorous, and the reason the automation still works in month six.
- 04week 4
Build and evaluate the judgement steps
Classification or extraction, scored against a labelled set from your own history, with an agreed accuracy threshold and a fallback to a human below it.
- 05week 5
Shadow run
It runs alongside the manual process without acting, and you compare outputs. Disagreements are the tuning list.
- 06week 6
Cut over and hand off
Staged rollout, dashboards, runbooks, and a recorded walkthrough for whoever will own it.
From $4,500 for a single process, $4,500 to $7,500 for a suite covering a workflow end to end. Running cost is typically $60 to $250 a month on your own accounts. See pricing for what moves the number.
Where the workflow needs to plan rather than follow a route, see AI agent development. Agencies reselling automation should start at white-label AI development.
Frequently asked questions
Often, yes, and we will say so. Those tools are excellent up to a point, and that point is usually reached when you need error handling that survives a failed third step, per-record state, real testing, or volume that makes per-execution pricing painful. Below that line, use them - a workflow you can maintain yourself is worth more than one you have to call us about.
Only where judgement is needed - classifying a message, extracting fields from an unstructured document, deciding which of five routes a case takes. Everything else should be ordinary code. An automation that calls a model for something a regular expression could do is slower, costlier and less reliable.
Retries with backoff for anything transient, a dead-letter queue for anything that keeps failing, and an alert to a human with enough context to fix it. Every run is logged and replayable. This part is most of the engineering, and it is what separates an automation you trust from one someone checks every morning.
Four to six weeks for a suite covering one workflow end to end, less for a single process. The first week is spent watching the process as it actually runs, which is usually different from how it is documented.
$60 to $250 a month for most automation at moderate volume, on your own accounts at cost. Where AI is only in the judgement step rather than every step, running cost stays low and predictable.
Usually it replaces the worst hours of a job - copying between systems, re-keying data, triaging a queue at 8am. Be straight with your team about what is changing; automations that arrive as a surprise get quietly worked around, and then you have paid for something nobody uses.
Name the hours
Tell us which process is eating them and how many. We will tell you whether it needs engineering or a connector.