AI Business Automation
Workflow automation for the approvals, hand-offs and multi-step processes that currently run on email and memory.
What you get
Some processes aren't hard, just long. A new supplier needs a vendor record in NetSuite, a folder in Google Drive, bank details verified, a welcome email sent and an approval from finance. A refund over a certain value needs a manager's yes before it's issued in Shopify. Each step is simple. The trouble is keeping track of where everything is, and who's waiting on whom.
Our workflow automation work turns these processes into a defined sequence that runs on its own. A trigger starts it, each step hands off to the next, approvals arrive as a message with buttons in Slack or Microsoft Teams, and the whole thing is logged so you can see which stage any request is at.
We build on Make, n8n or Zapier when the workflow suits a visual tool your team can maintain, and on custom code when it needs more control. Where a step involves reading free text, such as a request form filled in by a non-technical colleague, we add an AI step to structure it before the rules take over.
Workflow automation is one part of our wider AI business automation service, and it often pairs with document processing when the process starts with a PDF.
The problem
Ask how a process works and you'll often hear, "Sarah handles that." When Sarah is on holiday, the process stops. Requests sit in an inbox, nobody knows whether finance has approved the new laptop order, and the onboarding checklist for a new hire is half done.
Multi-step processes break down in predictable places: at hand-offs between people, at approvals, and at the point where data moves from one system to another. Email is a poor tool for this. It has no status, no deadline and no way to tell you which of forty threads are still waiting on someone.
The fix isn't a new project management tool. It's turning the process into something that runs itself, stops only when a person is genuinely needed, and shows everyone where things stand.
What we build
Workflows start from real events: a form submission, a new row in a sheet, a deal moving stage, a webhook from Shopify or a file arriving in a folder.
Approvers get a Slack or Teams message with the details and buttons to approve or reject. The workflow waits, sends reminders and escalates if nobody answers.
Data is created and updated across your tools in one run, so a new customer exists in the CRM, the accounting system and the shared drive at the same time.
Requests written in plain language are turned into structured fields by a model, then validated by rules before anything happens downstream.
Each step can have a deadline. Late items are flagged, reassigned or escalated automatically instead of being discovered a week later.
Every run records who approved what and when, which helps with internal controls and answers the inevitable 'who signed this off?' question.
Examples
A buyer fills in a short form. The workflow creates a draft vendor in NetSuite, asks finance to verify bank details in Teams, creates a Drive folder, sends the supplier a welcome pack and marks the vendor active only once every step is complete.
A support agent requests a refund in Gorgias. Small amounts go straight through. Anything above a set limit sends a Slack message to a team lead with the order history attached, and the refund is issued in Shopify once approved.
When a hire is marked as accepted in the ATS, accounts are requested in Google Workspace or Microsoft 365, IT gets an equipment ticket, the manager gets a first-week checklist and payroll gets the details it needs.
A client emails a new request. AI extracts the scope, deadline and client name, a project is created in the PM tool with the right template, and the account lead confirms the assignment in one click.
How we build it
We start by writing the workflow down as it should run: the trigger, each step, who owns it, what counts as done and what happens when something goes wrong. Agreeing on that on paper first avoids most of the rework later.
For most approval and hand-off workflows, Make or n8n is the right fit. They have connectors for the common tools, they're readable by non-developers and they handle waiting for a human response well. We use Zapier when your team already runs on it. We use custom Node.js services when the workflow involves complex branching, high volume or systems without connectors, often alongside the platform rather than replacing it.
When a workflow also touches your sales pipeline, we usually coordinate it with CRM automation so both share the same rules. For an overview of how operations teams use this, see our operations solutions, and for the steps of an engagement, our process.
It depends on volume, complexity and who will maintain it. Zapier is simplest, Make handles branching well, and n8n can be self-hosted for cost or data control. We'll recommend one based on your workflows rather than a default preference.
Yes. We build approval messages for whichever chat tool your team actually uses, and email approvals are possible as a fallback for external approvers.
Each approval step has a timeout. The workflow sends a reminder, then escalates to a backup approver or flags the request in a status view, depending on the rules you choose.
For no-code builds, yes. We name and document each step so an ops person can adjust thresholds, approvers or messages. Structural changes are easier with a quick call, and we're happy to help.
Often not. Many approval and hand-off workflows are pure rules. We add an AI step only where input is unstructured, like a free-text request or an email, and it needs to be turned into fields first.
Describe the steps and where things stall. We'll come back with a plan for automating it and an honest view of what should stay manual.
We pick tools for your situation, not ours. These are the ones we reach for most on this kind of work.
How we designed a Shopify app that syncs supplier stock and prices from any file or API, shows a diff before writing, and refuses to import files it doesn't trust.
Read the storyHow we turned a Google Form, a serial-number spreadsheet and a claims inbox into one Shopify app that registers units, issues coverage and resolves claims with real Shopify objects.
Read the storyHow we built a WooCommerce plugin that takes a quote from an Add to Quote button through PDF quotations and negotiation to a paid order, without leaving the store.
Read the storyWe don't just build for clients. These are our own products, used by real stores. See all products.
Human-in-the-loop design lets you put AI to work on real processes while people stay in charge of the decisions that matter. Here are the patterns, thresholds and review screens that make it work.
A step-by-step method for estimating the ROI of an automation project before you build it and measuring it honestly afterward, with a clearly hypothetical worked example.
How AI document processing turns invoice and purchase order PDFs into validated, structured data in your ERP or accounting system, and the checks that keep it accurate.
Tell us how it works today. We'll tell you honestly what's worth automating, what it would take, and what it would cost.
