Automation for high-volume workflows.
Automate the repeatable parts of intake, routing, and document-heavy processes, while decisions and exceptions stay with the people accountable for them.
| Good for | High-volume, repeatable workflows |
|---|---|
| Engagement | Scoped project or $200 / hour |
| First step | A short brief by email. Free. |
What the work involves
AI automation earns its place where inputs vary: emails, call transcripts, documents, customer requests. Deterministic rules still belong in conventional software. I use each where it fits, and measure the result against a baseline.
- Classify incoming requests and route them to the right queue or team.
- Extract fields from emails and documents, and validate the required data.
- Draft replies and follow-up tasks using account context.
- Update approved records and route exceptions for human review.
When it helps
A repeated task has enough volume to matter, follows a recognizable process, and has historical examples we can use to test the result.
A typical project
An incoming email contains a customer’s address, service need, and preferred timing. The automation extracts the details, checks for missing information, and prepares a CRM record and a reply. A person reviews the draft before it’s sent.
What you get
| Deliverable | What it includes |
|---|---|
| A mapped workflow | The trigger, inputs, rules, exceptions, and current baseline for the process. |
| A tested automation | The agreed workflow connected to your systems, with review steps and structured logs. |
| Measures that matter | Tracking for handling time, correction rate, completion, and missed follow-ups. |
Questions
Does every automation need AI?
No. Where fixed rules handle a task reliably, conventional automation is simpler to operate. AI is useful when inputs vary or the task requires interpreting language.
Will this replace the whole process?
The first scope is usually one stage of the process. We establish a baseline, test the automation, and review results before expanding.