Where does the manual work sit?
Pick one process, such as credit applications, claims or policy referrals. Enter its monthly cases and the fully loaded cost of handling an exception manually.
Everything entering this process, including cases already automated.
Cases completed without a person today.
Average fully loaded handling cost, in USD.
Including exceptions resolved by governed agents with no human touch.
Cases still decided by a person arrive already investigated.
How much more work enters this process each year.
Example values are prefilled and every figure is editable. Nothing you enter leaves this browser.
Same cases. More of them completed.
Existing automation stays in place. Agents resolve eligible exceptions within the authority the business delegates. The rest still go to a person, with the investigation done.
Straight through processing rises from 70% to 85%: 15,000 more cases a month completed without a person.
Monthly cases at today's volume. Every case a person still decides keeps an accountable human in the loop.
What your exception queue could stop costing you
Two savings: exceptions that agents now resolve no longer need a person, and the ones people still decide take less time because they arrive already investigated. Both are savings in manual processing cost, before the cost of the solution.
Where the first year comes from
Each exception is counted once.
What manual processing costs each year
The gap between the lines is the saving. Volumes grow at your rate; rates and unit costs stay fixed.
Year by year figures
| Year | Annual cases | Today's model | With agents | Saving |
|---|
Modelling assumptions. All figures are indicative, in USD and exclude taxes. Savings are in manual processing cost, or capacity released, before the cost of the solution. They are not guaranteed cash savings, net return or total cost of ownership. It excludes design, delivery, integration, hosting, AI inference, governance and ongoing supervision costs, and assumes the target rate and effort saving apply from Year 1 with unit costs held flat. Actual results depend on which exceptions are eligible, decision quality, controls, adoption, and how released capacity is realised.
Autonomy, with accountable boundaries
The value sits in exception queues. Capturing it means deciding which decisions agents may make, and when they must involve a person.
Going beyond existing STP limits
The same 100 cases under today's rules and with a governed exception agent, including the work that stays with people.
See the STP modelProve it on your own cases, in weeks
What sets us apart, and how we get a governed agent working on one of your exception queues, safely, in your environment.
See how we helpWhich exception queue would you tackle first?
Midships combines process redesign, governed agent delivery and Icebreaker runtime governance (patent pending). We will test the opportunity against your own cases and the controls it needs.