Savings calculatorSTP explainedWhy Midships
Why Midships

Prove it on your own cases in weeks, not months.

Most organisations can see the value in their exception queues. What stops them is the time and risk of getting an AI agent close enough to real decisions to prove it. We bring everything needed to do that safely, running in your environment, with your data and your model.

On premisesor in your own cloud tenancy, in country
Your modelworks with the language model you already use
Plugs inalongside your identity platform and API gateway
1. What is different

Most platforms give you an agent. We give you one you can trust with a decision.

Building an agent is the easy part. The hard part is everything a regulated business needs before it will let that agent act, and that is usually left for you to build.

What a governed agent needs
Typically
With Midships
A formal appointment
An agent has an identity and access. What it has been entrusted to do lives in prompts and documents.
Every agent works under a persona: its purpose, capabilities, scope, who approves and who is accountable. Owned and certified by the business, versioned, and revocable everywhere at once.
The right action, not just a permitted one
Access controls confirm the agent may call a system. Nothing checks whether it should.
Every consequential action is checked against the purpose and intent it was approved for, before it executes.
A person where it matters
Escalation is custom work, so agents are kept away from real decisions.
Anything beyond delegated authority goes to an accountable person, with the case already prepared.
Evidence
Logs show what happened.
Every decision is recorded with its reasoning, whether allowed or denied, ready for risk, audit and your security operations tooling.
If something goes wrong
Depends on how the agent was built.
It fails closed: if a check errors or is bypassed, the action does not run.
Somewhere safe to prove it
An integration project before anything can be tested.
A ready end to end environment, from front end through API gateway to a mock MCP server, so the proof starts with decisions, not plumbing.
2. How it decides

Semantic alignment: is this action still what the business asked for?

Before an agent acts, Icebreaker, our runtime governance engine, checks the action against four things the business approved. If every layer holds, it goes ahead. If not, it goes to a person or is stopped.

  1. PurposeWhat the agent was appointed to doResolve credit card application exceptions
  2. ObjectiveThe outcome it is pursuing nowDecide this applicant's limit
  3. IntentWhy this step serves that outcomeConfirm income before setting a limit
  4. ActionThe specific call it wants to makeRead the applicant's verified income record
ALLOW

Within everything approved. It runs, and the reasoning is recorded.

APPROVAL REQUIRED

Sensible, but beyond delegated authority. A person decides, with the case prepared.

DENY

Outside what the agent may ever do. Stopped and recorded.

A governed agent can still be wrong. The difference is that every decision is bounded, attributable and reviewable, so a wrong one is contained, traced and corrected.

3. Proving it

One exception queue, your cases, real AI

A proof that a risk committee can take seriously, because it runs the way production would: in your environment, under the same controls, without touching a live system.

  1. Choose the queueYour business picks one exception process and the decisions it expects, using your own test cases.
  2. Appoint the agentsWe build the personas: what each agent may decide alone, and what goes to a person.
  3. Run it for realReal agents on your model, governed end to end, working against our mock MCP server instead of your production systems.
  4. Measure itExceptions resolved without a person, exceptions still needing approval, and decisions people overturned.
  5. Connect itWhen the evidence supports it, we deploy into your environment and integrate with your systems.

What we need from you: a business sponsor who will own the authority the agents are given, and early involvement from security, because the controls are at the heart of it.

Where we are: Icebreaker is patent pending. Pilots and proofs of value are in progress with regulated enterprises, and it can be deployed today on premises, in your cloud tenancy or in country.

Pick one exception queue. We will prove it on your cases.

Start with the savings calculator, or talk to us about the queue that hurts most.