Stop doing the same task thirty times a week.

Every business has them: the workflows that run on autopilot in everyone's head, not in any system. Client intake. The monthly client report. The invoice that needs three approvers before it goes to AP. The proposal that gets rebuilt from scratch every Wednesday.

Each individual step is small. The cost is in the joins between them, the email that sits unanswered for two days, the spreadsheet someone forgot to update, the document that bounces between three drafts because the template was last refreshed in 2023.

Off-the-shelf tools rarely fit because the workflow is yours. Generic CRMs assume one shape. Generic automation tools assume another. What you actually need is a pipeline built for the way your team works, integrated with the systems you already use.

Most workflows fit a pattern: capture an input, classify it, route it down a path, take an action. The art is in getting each step right for your workflow, not a generic one.

A typical build looks like this:

• Capture, every incoming signal (form, email, API call, file drop) lands in one place within seconds, with a structured record created automatically.

• Classify, the AI reads it, categorises it against criteria you've specified, and writes its judgement back to the record. A human reviews the classification, not the raw input.

• Route, the classified record goes down one of several paths. Each path is a small, named set of rules, not a sprawling logic tree.

• Action, the system drafts whatever needs drafting (reply, document, notification), and a human approves it before it ships. The bottleneck collapses; the quality control stays.

What you get at the end is not a tool subscription you have to learn. It's a system that runs in the background, that your team uses without noticing, that you own.

A worked example: a small professional-services firm doing ten new client enquiries a week. The current intake process involves eight manual steps, initial reply, qualification, calendar booking, discovery call notes, proposal drafting, engagement letter, matter setup, kickoff. Two days of someone's week, every week.

After the build, the same intake runs with two manual touchpoints: a human reads and clicks send on the AI-drafted reply, and a human edits the proposal before it goes out. The other six steps run in the background. Total active time per lead: under two minutes. Lead-to-reply: under ninety minutes instead of twenty-four hours.

The numbers vary by workflow and by firm. The shape doesn't. Wherever there's a repeatable process being done by hand, the same compression is achievable.

A good fit if:

• You have a workflow that runs at least ten times a month.

• The current process is documented, or documentable in an afternoon.

• You have a system of record (CRM, spreadsheet, practice-management tool) the automation can read from and write to.

• You're comfortable with the AI drafting outputs that a human reviews before they ship.

Probably not the right move if:

• You're trying to automate sales prospecting (different problem, different stack).

• You need RPA to control someone else's UI, that's a different category of build.

• The workflow involves regulated decisions that genuinely require partner-level human judgement at every step.

• You don't yet have a clear sense of which workflow you'd start with.

That last one is fixable. Run the free site audit and tell me the manual task you'd most like gone, we can use that as the starting point.

Part of the wider AI implementation work I do. The other outcome lanes:

• Custom AI agents, for tasks that need reading and thinking, not just execution.

• Data extraction, for pulling structured data out of PDFs, statements and web pages.

Working in a specific sector? For agencies