Put autonomous AI into production, and trust it.
We govern agent action in customer facing and revenue critical workflows with the accountability, control and evidence regulators require, enforced through the identity controls we already operate for tier one banks.
Any IAM platform
Keycloak and Ping ready
MCP compatible
Audit by default
Static workflows automate the predictable and escalate the rest. Agents break that ceiling by reasoning toward an outcome rather than following a script, which is exactly why each action they take has to be checked against an approved purpose before it executes.
Most enterprises have autonomous agents working in internal copilots and almost none in live customer workflows. The reason is not capability. It is accountability. Existing controls tell you who an agent is and what it may reach. None tell you whether the action it is about to take is right for this session, right now. Until that question can be answered and proven, a regulated business cannot let an agent act on a customer's money, data or entitlements.
We govern what we operate.
Three things combine to make autonomy safe in production.
Guardian · 24x7 trust operations
Icebreaker · patent pending
Enterprise systems and data
Core banking, customer data, money movement, entitlements, APIs.
Identity and context layer
Your identity layer: Ping, Keycloak, CIAM, workforce and non human agent identity. The policy enforcement point Icebreaker enforces through, whether or not Midships operates it.
ICEBREAKER · runtime purpose and intent governance
Patent pending. The action is evaluated before it executes.
System Purpose
Validated mandate, registered.
Objective
Session goal versus purpose.
Intent Set
Planned operations validated.
Runtime Action
Enforced at the PEP.
Autonomous AI agents
Copilots, customer assistants, multi agent orchestration, third party agents.
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Intent
Decision
Action
Evidence
Evidence out to the EU AI Act, Forrester AEGIS, ISO 42001, MAS TRM and DORA.
Icebreaker, our patent pending runtime governance layer, evaluates every agent action against an approved business purpose before it executes, and records a tamper evident chain from purpose to action. It allows, blocks, modifies or escalates in real time.
The Midships Enterprise AI Agent Reference Architecture defines the full stack for governed autonomy, from the model platform up through the identity and metadata context layer to the governance layer. It gives your architects a blueprint, not a slogan.
Icebreaker enforces through your existing policy enforcement point, the IAM platform you already run, whatever it is, including Ping and Keycloak, with no replatforming and no IAM replacement. Some integration work, including new APIs in some environments, may be required. It works whether or not Midships operates that layer. Where Midships does operate your identity layer, the advantage compounds. Governance is built into systems we already run in production and are already accountable for, rather than bolted on afterwards by people who have never operated them. That is an option we offer, not a precondition for Icebreaker.
The payoff is largest in complex, variable and exception heavy work, where a static workflow would force you to anticipate every permutation in advance. Customer service and case resolution, fraud and investigation, and cross domain processes with many possible paths. Because the agent constructs the workflow for the specific customer case rather than selecting a pre built one, you no longer have to design and maintain every permutation. High volume, well defined and irreversible processes are better left to deterministic workflows, which is the layered model Icebreaker is built to govern.
Trusted Autonomy – FAQs
How do you put autonomous AI agents into production safely?
Midships governs each agent action against an approved business purpose before it executes, through Icebreaker, our patent pending runtime governance layer. It allows, blocks, modifies or escalates in real time and records a tamper evident chain from purpose to action, enforced through your existing identity controls.
What stops most AI agents from reaching production?
Accountability, not capability. Existing controls tell you who an agent is and what it may reach, but none tell you whether the action it is about to take is right for this session, right now.
Does Icebreaker replace my identity provider?
No. Icebreaker works with all identity and access management platforms and enforces through your existing controls, with no replatforming and no IAM replacement. Some integration work may be required, including new APIs in some environments, but Icebreaker adds the purpose and intent layer your controls do not have rather than replacing them.
Which workflows benefit first?
The payoff is largest in complex, variable and exception heavy work, where a static workflow would force you to anticipate every permutation in advance. Customer service and case resolution, fraud and investigation, and cross domain processes with many possible paths. Because the agent constructs the workflow for the specific customer case rather than selecting a pre built one, you no longer have to design and maintain every permutation. High volume, well defined and irreversible processes are better left to deterministic workflows, the layered model Icebreaker is built to govern.
How is agentic orchestration different from RPA or workflow automation?
RPA and workflow automation execute a predefined path and break or escalate when reality departs from it. Agentic orchestration reasons toward an outcome and builds the workflow for the case at runtime, so it handles the variation and the permutations a fixed flow cannot. The trade off is control, because a runtime generated plan has no pre approved specification, which is why Midships governs each plan with Icebreaker before it becomes a business action.