Outcomes
Automate my workflows
Take off your team's plate the work a machine does better precisely because it never varies.
In almost every company there is a competent person spending six hours a week copying information from one system into another. It is not an effort problem — it is a design problem, and the real cost is not the time: it is the error that creeps in when someone mistypes a line at five in the afternoon.
But there is a trap worth naming before money is spent: automating a bad process is accelerating the problem. The work starts by understanding the process, deciding what no longer needs doing, and only then building. Anyone who starts building in week one delivers faster and solves less.
What can be delivered
- A map of the current process, with the hours each step costs — often this is where the decision changes
- Integrations between the systems you already use, without replacing them
- Automations that log what ran and what failed, and alert a human when they do
- AI agents where judgement is needed but repeatable, with defined limits and escalation to people
- Documentation and training, so the automation does not depend on whoever built it
- Before-and-after measurement, in hours and in errors, so you know whether it paid
The skills this mobilises
How long it takes
Two to three weeks to map and prove one process; six to twelve for an operation with several connected ones. It pays to start with one and measure it before buying the rest.
When this is the right outcome
Choose this when the same manual work repeats every week and already costs more in hours than automating it would. Do not choose it for a process that changes monthly: automating something still being invented is building on sand.
Other outcomes
Tell us the problem. We'll tell you who solves it.
Half an hour of conversation. If it isn't work for us, we say so in that conversation.