Routine goes to machines
We find the processes that eat your team’s hours and automate them with LLM workflows: research, reports, content, document processing, CRM enrichment. Measured in saved hours, not buzzwords.
Automation measured in hours saved
The first 90 days
The quote is fixed before we start
Estimate the cost in 10 seconds
Related cases
AI automation: which processes to hand to machines first
The honest ROI checklist
A process is a good automation candidate when it repeats weekly, follows rules a smart intern could learn, and eats hours of someone whose time costs real money. Everything else is a demo, not a business case.
Our audit week produces a ranked list: hours saved × hourly cost − automation cost. We build only what’s positive within a quarter.
Stack, safety and human control
We build on n8n or Make with GPT/Claude — visual workflows your team can read and later edit. Every risky step gets a human approval gate: AI drafts, people confirm.
In the logistics case, automated quoting and CRM entry saved 520 hours a year — the build paid back in under two months.
Often ordered together
Frequent questions
Which processes should we start with?
How much does automation cost?
Is our data safe?
What if the AI makes a mistake?
Will we depend on you forever?
Quick answers
Get your automation map
Describe a routine that annoys the team — we’ll reply with a workflow sketch, saved-hours estimate and price.