AI Governance for Regulated Enterprises
Autonomous AI introduces
enterprise risk
your current controls cannot manage
Midships enables AI agents to operate safely in production without constraining their capability. Runtime enforcement, audit-ready governance, and no changes to your existing systems. Powered by Icebreaker — the control plane for governed AI execution.
70M+
Identities secured
7+
Years in regulated IAM
3
Regions — APAC, UK, Middle East
0
Downtime delivery model
The Governance Gap
Without runtime governance, AI agents will be blocked or over-permissioned. Both outcomes destroy ROI.
For a Tier 1 bank, the question is not whether to deploy agentic AI. It is whether you can deploy it without creating regulatory exposure, audit failure, or reputational risk. Your current IAM controls were not designed for this.
RBAC and ABAC enforce what a system is permitted to do. They do not evaluate whether what it is about to do is aligned with the business purpose it was authorised for — in the current session, at the moment of execution. That gap is where autonomous AI becomes an enterprise liability.
EU AI Act Article 9, MAS TRM, and FCA expectations all require explainability, auditability, and ongoing risk management for AI systems operating in regulated processes. Most enterprises cannot demonstrate this today.
What is missing in most deployments
No purpose boundary
No enforceable declaration of what the AI system is authorised to do. Scope creep is invisible until it causes an incident.
No session accountability
Each execution run has no governed scope. You cannot prove that a specific action was within an authorised workflow.
No runtime enforcement
Actions are permitted or denied on static permissions, not real-time evaluation of intent, context, and policy alignment.
No audit trail
AI actions are not logged in a form that satisfies risk or compliance requirements. Evidence is absent when needed most.
No separation of duties
The same team that builds the AI controls what it is allowed to do. There is no independent governance layer.
What Effective Governance Requires
Four non-negotiable controls
For regulated enterprises deploying agentic AI in customer-facing or revenue-critical processes, these are the baseline requirements.
01
Purpose control
Every autonomous AI system must operate within a validated, persistent declaration of what it is authorised to do. This is not a prompt or a system message. It is a governed artefact — stored, versioned, and enforced.
02
Session accountability
Every execution run must be scoped to a declared goal evaluated for alignment with the system's authorised purpose before it begins. Sessions must be bounded and traceable end to end.
03
Runtime enforcement
Every action an AI agent proposes must be assessed in real time against approved intent and policy context before it executes. Decisions must be made before actions land — not after an incident has already occurred.
04
Audit by default
Every governance decision must generate a record with context, policy reference, and outcome. Evidence must be available without additional instrumentation — ready for internal risk review or regulatory examination.
Enterprise AI Agent Reference Architecture
Deploy governed AI in months, not years
Most enterprises stall on AI deployment because they cannot agree on where governance fits in the stack. Midships has solved this. The Enterprise AI Agent Reference Architecture is a modular blueprint — adopt the layers you need now, extend over time. No rip-and-replace. No new IAM platform. No API changes to existing systems.
API Gateways & Policy Enforcement
WFM & CIAM
Audit, Traceability & ObservabilitY
Experience Layer
Governance & Control Layer
Identity & Metadata Context
Integration Layer
Agent Platform Layer
* Identity Governance for Agents can be part of WFM. Detailed reference architecture documentation is available on request.
Integrates, does not replace
Core IAM capabilities — agent identity, delegation, dynamic authorisation, consent, and cross-domain identity — remain provided by your existing ID&A stack. The Midships architecture integrates with these services and introduces an additional governance layer to manage agent purpose, intent, and runtime action control.
Architecture and Roadmap
A complete reference architecture document — covering agent identity model, enterprise metadata management, policy and governance architecture, gateway and MCP integration, monitoring, and operational ownership — is available for enterprise engagements. Contact sales@midships.io to request it.
Alignment with Zero Trust
01
Discovery and Assessment
Every AI agent has a registered identity in the IAM platform. Actions are attributed to a verified agent acting within a governed session — never anonymous or assumed.
02
Least Privilege Execution
Agents operate within the minimum scope required for their approved session purpose. Icebreaker enforces intent-level boundaries so agents cannot exceed their authorised operational scope.
03
Continuous Runtime Verification
Every action is assessed at the moment it is requested — not assumed safe based on prior approval. Governance is continuous across the full session lifecycle.
Regulatory Direction of Travel
IAM and AI governance for regulated enterprises
Midships specialises in three capability areas. Each is relevant to regulated enterprises deploying or operating identity and AI systems in production.
EU AI Act
Architecture, implementation, migration, and 24x7 managed operations for Ping AIS (PingAM, PingDS, PingIDM, PingAuthorize) and Ping AIC (PingOne). Zero downtime delivery. Trusted by tier-one banks across Asia Pacific, the UK, and the Middle East.
MAS TRM & AI Guidelines
Enterprise Keycloak and Red Hat Build of Keycloak — solving the HA, upgrade, and advanced journey problems that out-of-the-box Keycloak leaves unresolved. Production-grade deployments in regulated environments with full zero-downtime upgrade procedures.
FCA AI Framework
When AI moves from answering questions to taking actions, standard access controls are not enough. Midships provides AI governance strategy, reference architecture adoption, and Icebreaker — our runtime governance product for autonomous AI in regulated environments.
DIFC & ADGM
When AI moves from answering questions to taking actions, standard access controls are not enough. Midships provides AI governance strategy, reference architecture adoption, and Icebreaker — our runtime governance product for autonomous AI in regulated environments.
DORA
When AI moves from answering questions to taking actions, standard access controls are not enough. Midships provides AI governance strategy, reference architecture adoption, and Icebreaker — our runtime governance product for autonomous AI in regulated environments.
NIST AI RMF
When AI moves from answering questions to taking actions, standard access controls are not enough. Midships provides AI governance strategy, reference architecture adoption, and Icebreaker — our runtime governance product for autonomous AI in regulated environments.
What We Do
IAM and AI governance for regulated enterprises
Midships specialises in three capability areas. Each is relevant to regulated enterprises deploying or operating identity and AI systems in production.
AI Governance Strategy
Readiness assessment, risk mapping, and governance architecture design. Scoped to your regulatory context and technology stack.
Reference Architecture Adoption
Implementation of the Midships Enterprise AI Agent Reference Architecture against your existing IAM and integration estate. Where components are not yet defined, the reference architecture acts as the working baseline.
Icebreaker Deployment
Full deployment of the Icebreaker runtime governance product, from environment setup through to production rollout. Available as standalone or part of a broader managed programme.
Regulatory Evidence Design
Audit trail design, evidence pack structure, and reporting frameworks for risk, compliance, and regulatory teams.
Managed Governance Operations
Ongoing managed operations covering policy management, alert response, governance reviews, and SLA-backed monitoring.
Training and Enablement
Governance bootcamps and game days for security, risk, and technology teams — live-fire simulation of agentic AI governance scenarios.
The Runtime Governance Product
Icebreaker — the Governance and Control Layer
Icebreaker is the control plane for governed AI execution — a patent-pending product from Midships. It implements the Governance and Control Layer of the Enterprise AI Agent Reference Architecture, ensuring every AI-initiated action is aligned to an approved business purpose, enforced through existing enterprise controls, and recorded for audit before execution. No replatforming. No IAM replacement. No API changes.
Frequently Asked Questions
AI Governance — common questions
What is AI governance and why does it matter for regulated enterprises?
AI governance is the set of controls that ensure autonomous AI systems operate within authorised boundaries, that their actions are accountable, and that evidence of compliance is available for audit and regulatory purposes. For regulated enterprises it is increasingly a compliance requirement as regulators develop mandatory frameworks for AI in financial services.
How is AI governance different from traditional identity and access management?
Traditional IAM enforces static permissions for human users and predictable software. AI governance addresses autonomous agents that make sequences of decisions at runtime — requiring purpose validation, session scoping, intent evaluation, and real-time enforcement before actions execute. These are complementary layers, not alternatives.
What is the Enterprise AI Agent Reference Architecture?
It is a complete layered model developed by Midships for deploying autonomous AI safely in regulated enterprises. The five layers are: Experience Layer, Governance and Control Layer, Identity and Metadata Context Layer, Integration Layer, and Agent Platform Layer — with API Gateways, WFM/CIAM, and Audit/Traceability running as cross-cutting concerns. Icebreaker implements the Governance and Control Layer.
Does the reference architecture replace our existing IAM platform?
No. The Midships reference architecture integrates with your existing IAM platform rather than replacing it. Core capabilities — agent identity, delegation, dynamic authorisation, consent, and cross-domain identity — remain provided by your existing ID&A stack. Icebreaker introduces an additional governance layer on top of these capabilities.
What regulations apply to AI governance in financial services?
The EU AI Act, MAS guidelines on AI in financial services, FCA emerging AI frameworks, DIFC and ADGM guidance in the Middle East, DORA, and NIST AI RMF all impose or are developing requirements for governed AI in customer-facing and financial contexts. Requirements vary by jurisdiction and use case.
Does Midships offer AI governance consulting or just a product?
Both. Midships provides governance strategy, readiness assessment, reference architecture adoption, and architecture advisory alongside Icebreaker as a deployable runtime governance product. Engagements can be scoped as advisory only, product deployment only, or a full managed programme.
How does Icebreaker relate to AI governance?
Icebreaker is Midships' purpose-built runtime governance product. It implements the Governance and Control Layer of the Enterprise AI Agent Reference Architecture — providing purpose control, session accountability, intent evaluation, runtime enforcement, and audit by default as a production-grade control plane.
How do we get started with AI governance at Midships?
Contact sales@midships.io for an initial briefing. Midships can conduct a governance readiness assessment scoped to your architecture and regulatory context, and recommend a deployment approach — whether advisory, product deployment, or a full managed programme.