Increase autonomous completion
Resolve more eligible exception cases without adding manual queues.
Enterprise AI
Make AI earn its place in the business.
Increase completed transactions, control what agents may do and deliver useful software reliably. Start with a measurable problem, not an AI programme.
Why you are here
When AI has to show a return.
These are the moments when a governed, measurable use case matters more than another pilot.
- A pilot worked but never reached production. Nobody could agree what the agent was allowed to do.
- Exception queues grow faster than headcount. Rules-based automation has done what it can.
- Risk or audit is blocking agents from acting. Without enforceable limits and evidence, the answer stays no.
- The board is asking what AI has delivered. You need a number, not a roadmap.
What changes
What should AI change for your business?
Reduce unchecked agent action
Enforce authority and retain evidence whenever an agent acts.
Improve delivery predictability
Control AI-assisted software engineering with testable, traceable output.
Where to begin
One outcome worth changing.
What exists today
Different stages of maturity. Clear boundaries.
Delivered capability
Identity and enterprise engineering
Production platform design, migration, integration and operations.
Scoped offering
Caravel
Controlled AI-led delivery for defined workloads, with traceability and independent review.
Pilot stage
Icebreaker and agentic STP
In active customer pilot.
See where agents make a difference.
Explore the existing-rules comparison and the governed refund walkthrough. Both show where an agent may act and where a person remains accountable.
See the STP comparison ↗Follow a governed decision ↗Common questions
Questions about autonomous AI.
Where should an enterprise start with autonomous AI?
Start with a costly, measurable business process or an agent action that carries real risk. Midships assesses the workflow, authority boundaries, systems integration and operational responsibilities before prescribing technology.
What is different about governed straight through processing?
Existing rules still handle standard cases. An Exception agent investigates cases that fall outside those rules and resolves only the cases within delegated business authority; others go to an authorised reviewer.
Is Icebreaker running in production at a tier 1 bank?
Not yet. The governed exception-processing solution is in an active customer pilot.
Next step
Discuss a governed AI use case Discuss a measurable AI outcome.
Tell us which process, cost or risk you want to change. We will assess where an agent adds value, what authority it needs and what evidence the business should retain.