Operations5 min
Name the process before you automate it
A badly designed process that runs faster is still a badly designed process. We start with how the work runs today.
About
Take repeating work out of the week.
Recurring work is usually not a tool problem. Intake sits in three inboxes, follow-up depends on who sees it, and the same file gets checked every week by someone who already knows the answer.
We write down how the work actually runs, exceptions included. Then we automate what does not need a person. If AI is the wrong tool for that job, we say so.
Operations now
78%
of organisations use AI in at least one business function
71%
regularly use generative AI in at least one function
60 to 70%
of employee time sits in activities that current technology can automate
22%
of CXOs report an active gen AI use case in a corporate function
Figures from McKinsey, The state of AI. 78% of organisations use AI in at least one function. 71% regularly use generative AI. McKinsey also estimates that current generative AI and other technologies can automate activities that take 60 to 70% of employee time. Rolling it into a corporate function is still rarer: 22% of CXOs report an active use case there.
Offerings
The work we take on.
What we build sits in the operation, not in a demo that summarises a PDF.
01
Process first
Tasks, hand-offs and exceptions go on paper before anything is automated. Skip that and you just speed up the mess.
02
Intake and follow-up
Incoming work gets classified and sent on. Reminders and status do not wait for someone to notice.
03
Rules, AI, or neither
When the outcome is clear we use rules. When the input varies we may use a model. When the risk is high, a person stays on it.
04
Control and handover
It connects to the tools you already use. After go-live there is logging, a way to stop the flow, and someone who owns it.
Insights
