AI Automation Consulting
Practical AI workflow automation across PM, ops, content, and CRM pipelines. Google AI Essentials certified.
Deliverables
- +Workflow audit — where AI actually saves time vs where it's theatre
- +Tool selection: Claude / GPT / domain-specific (n8n, Zapier, Make)
- +Prompt libraries scoped to your domain and tone
- +Quality control and human-in-the-loop checkpoints
- +Measurement framework (time saved, error rate, cost)
- +Team training so the team owns the workflow after I leave
When this is the right move
- →Ops teams doing high-volume repetitive cognitive work
- →PMOs spending hours each week on status report aggregation
- →Content / marketing teams shipping at higher cadence than headcount allows
Questions teams ask before they hire
What can AI actually automate well today?
Drafting (status reports, briefs, copy), summarisation (meeting notes, reports), classification (ticket triage, lead scoring), and extraction (data from documents, web). Anything requiring real judgment, novel reasoning, or stakeholder relationship remains human.
Do I need engineering to implement this?
Often no. Most PM and ops automation runs on no-code platforms (Zapier, Make, n8n) plus an LLM API. Engineering only comes in when you're building custom integrations or deploying internal tools.
How do you handle data privacy and IP concerns?
Default to enterprise-tier LLM contracts with zero-retention policies. For sensitive content, deploy via your own cloud or use models that run in your tenant. We design for compliance from the brief, not as a retrofit.
Let's talk.
Bring the project. I'll bring the structure, the cadence, and the calm.