AI Automation
AI workflow automation with n8n — built, hosted and maintained
We build the workflows that move documents, leads and data between your tools, with AI where it actually helps. Then we host them, watch them and fix them, so they keep running after the build.
What is AI workflow automation?
AI workflow automation connects your business tools so routine work happens on its own, with a language model handling the steps that used to need a person to read or write something — pulling data out of an invoice, sorting an email, summarising a call. The predictable steps run as plain automation; the AI steps handle messy, unstructured input. Anything uncertain goes to a person for review instead of slipping through silently.
Which workflows do we automate?
Document processing
Invoices, receipts and contracts read, checked and sent to your accounting or ERP, with a review queue for unclear items.
See the service →n8n hosting & maintenance
Self-hosted n8n kept running: monitoring, updates, backups and fixes, including workflows built by someone else.
See the service →Lead → CRM automation
New leads from forms, ads and email are enriched, scored and created in your CRM, with the right person notified.
See the service →Automated reporting
Numbers from several tools collected on a schedule and turned into a short written report your team actually reads.
See the service →Meetings → notes & tasks
Call recordings summarised, decisions captured and follow-up tasks created in your project tool.
See the service →Zapier or Make → n8n migration
Existing automations moved to n8n when cost, volume or data control make the switch worth it.
See the service →Who is AI automation for?
- Finance and admin teams typing invoice data into accounting software by hand.
- Sales teams whose leads sit in inboxes and spreadsheets before anyone looks at them.
- Agencies and consultancies spending Friday afternoons assembling client reports.
- Operations teams copying data between a web app, a CRM and a spreadsheet.
- Founders with a growing Zapier or Make bill, or automations nobody fully understands anymore.
Why do we build on n8n?
n8n is a workflow automation tool you can run on your own server or use as a hosted cloud service. We use it for most projects because:
- Data control. Self-hosted n8n keeps data on infrastructure you choose, which matters for documents, customer records and anything regulated.
- Cost at volume. Self-hosting means you pay for the server, not per task, so high-volume workflows don't get more expensive with every run.
- Code when it's needed. Visual building blocks for most steps, plus code steps for the logic that doesn't fit in a box.
- Built-in AI steps. Native nodes for language models, agents and vector stores, so AI steps sit inside the same workflow as everything else.
n8n isn't always the right choice, and we'll say so:
| n8n | Make | Zapier | |
|---|---|---|---|
| Hosting | Self-hosted or cloud | Cloud only | Cloud only |
| Pricing model | Server cost when self-hosted; per execution on cloud | Per operation | Per task |
| Ready-made app integrations | Many, plus any API | Many | The largest catalog |
| Custom code | Built in | Limited | Limited |
| Learning curve | Steepest | Moderate | Easiest |
| Best choice when… | Volume, complex logic, AI steps or data control matter | Visual, mid-complexity flows on a budget | A non-technical team needs simple app-to-app links |
If a handful of simple Zaps run fine and the bill is small, keep them. Migration pays off when volume, cost or data control become a problem.
How does an AI workflow work?
A trigger starts the workflow — a new email, a form submission, a file in a folder or a scheduled time. The workflow collects what it needs from your tools, uses a language model only for the steps that need reading or writing, checks the result against your rules, and sends unclear items to a person. The finished result lands in the right system, and every run is logged so failures are visible instead of silent.
What makes an automation reliable?
Most automations work on day one. The difference shows up months later, when a tool changes its API, a customer types something unexpected or the same email arrives twice. We build every workflow with:
- Logging of every run, so you can see what happened to any record.
- Error alerts that reach a person within minutes when a step fails, instead of failing silently.
- Retries for temporary problems, such as a tool being briefly unavailable.
- Duplicate protection, so the same invoice or lead isn't processed twice.
- A named owner and short documentation, so someone knows what the workflow does and why.
Skipping these is how automations end up "working" for weeks while quietly dropping data. They cost a little more to build and much less to live with.
What do we build automations with?
We name the tools we build with, but we aren't partners or resellers of any of them. When a workflow needs a front end — a review queue, a dashboard, a client portal — we build it in Bubble.io or Webflow.
How do we work on an automation project?
- Discovery call. We map the process as it really runs today, including the exceptions.
- Audit and fixed-scope proposal. We check the tools and their APIs, then send a written scope, timeline and price.
- Build and test with human review. We build on test data first, then run alongside the manual process until the results match.
- Launch and monthly care. We switch over, monitor every run, and keep workflows working as your tools change.
Payments are milestone-based: you pay after you approve each stage. Every launch includes one month of free bug fixing.
How much does AI workflow automation cost?
A typical automation project starts at $1,000, and hosting plus maintenance starts at $200 per month. What drives the price:
- Number of systems the workflow touches, and how good their APIs are.
- Exceptions. The happy path is quick; real processes have edge cases, and handling them is most of the work.
- AI steps. Reading documents or writing text adds model costs and needs review rules.
- Hosting choice. Self-hosted n8n needs a server and care; n8n Cloud shifts that cost to a subscription.
Is AI automation right for you?
Good fit when…
- The same manual steps repeat every day or week
- Your tools have APIs or at least export data
- Mistakes from manual copying are costing you
- You want the data to stay under your control
Not a fit when…
- The process changes every time it runs
- It happens a few times a month and takes minutes
- The tools involved have no way to share data
- Nobody can describe what "done right" looks like
Frequently asked questions
What is the difference between n8n, Make and Zapier?
All three connect apps and automate tasks. Zapier is the easiest to use and has the largest catalog of ready-made integrations; Make offers a visual builder at a lower price per operation; n8n can be self-hosted, supports custom code and has built-in AI steps. n8n suits complex, high-volume or data-sensitive workflows, while Zapier suits simple links managed by a non-technical team.
Why self-host n8n instead of using n8n Cloud?
Self-hosting keeps your data on servers you choose and replaces per-execution pricing with a fixed server cost, which helps at high volume. In exchange, someone has to handle updates, backups and monitoring. For one or two simple workflows, n8n Cloud is usually the easier choice.
How much does an AI automation project cost?
At Webziper, a typical automation project starts at $1,000, with hosting and maintenance from $200 per month. The price depends mostly on how many systems are involved, how many exceptions the process has, and whether AI steps such as document reading are needed.
How long does it take to build an AI automation?
A typical workflow takes 1–3 weeks from discovery to launch, including a period running alongside the manual process to check the results. Workflows that touch many systems or need approval steps take longer.
Can you take over automations someone else built?
Yes. We review existing n8n, Zapier or Make workflows, document how they work, fix what's broken and either maintain them as they are or move them to n8n when that makes sense. The review comes first, so you know what you're inheriting before you commit.
Is someone copying data between tools every day?
Walk us through the process. We'll tell you what can be automated, what should stay manual, and what it would cost.
Book a Free Call →