Governed agentic AI
The agentic AI platform for building enterprise AI agents.
Deterministic where it must be.
Autonomous where it should be.
Design, govern and run AI agents that live inside your own tenant, act under policy you define, and leave an audit trail you can replay step by step.
- Runs in your cloud, VPC or data centre — data never leaves it
- Fixed annual subscription — nothing metered
- Every run replayable end to end
The gap
Enterprises don’t have an AI problem.
They have an accountability problem.
Getting a pilot working is easy, and most enterprises now have several. What stops them reaching production is that nobody can say who approved the action, what the agent was looking at when it decided, or what happens when it gets one wrong. MouRio is built around answering those three questions.
It runs where your data already is
Deploy MouRio inside your own Azure, AWS or GCP subscription, your VPC, or your data centre — including fully disconnected environments. Data never leaves your boundary because the platform was never on the other side of it. That also removes the egress round-trip a SaaS agent pays on every step, which is why agents run at near-instant speeds when they sit next to the systems they are querying.
- Your subscription, your keys, your network
- No perimeter crossing, so no inspection latency per hop
- Air-gapped deployment supported
Policy is evaluated before the action, not after the incident
Each agent carries a policy pack: the tools it may call, the limits it must respect, and the actions that require a named human approver. Every action is checked against it before execution — so an agent that should not issue a credit note simply cannot, regardless of what the model decides.
- Per-agent tool allow-lists
- Named human approvers on sensitive actions
- Escalation routing when limits are exceeded
You can re-open any run and watch it happen
Every run records the input, the retrieved context, each tool call with its arguments and result, the model's responses, every policy evaluation and every human intervention. Re-open a run from months ago and walk an auditor through exactly what the agent did and why.
- Step-by-step replay of completed runs
- Source citations back to the originating document
- Cost and latency attributed per agent and per run
Platform
One control plane for the whole agent lifecycle
Design, govern, deploy and monitor agents from one place — instead of assembling a studio, a registry, an approval workflow and an audit trail yourself.
Agent Studio
Compose agents and multi-step workflows visually, with reusable components. Process owners build; engineering reviews.
AI Control Tower
Every agent, run, escalation and cost in one view — with a registry recording who owns each agent and which version is live.
Policy & Guardrails
Business rules, approval workflows and limits expressed as configuration and enforced at execution time.
Data Ontology
Shared, governed meaning for the entities your agents touch, so decisions are grounded in consistent context.
Agent-to-Agent Orchestration
Specialist agents hand work off to each other, with shared context and policy carried through every handoff.
Knowledge & Retrieval
Governed vaults over your documents and systems, with citations that open at the exact source page.
From process to production
Live in weeks,
governed from day one
Every stage produces something concrete, and nothing executes autonomously until you have measured it against real work.
01
Map the process
We capture how the work is actually performed — the rules, the decision points, the exceptions and the systems involved.
Deliverable: Process blueprint
02
Encode the guardrails
Your policies, approval thresholds and compliance constraints become the agent's policy pack.
Deliverable: Policy framework
03
Run in shadow mode
The agent proposes alongside the existing process while you measure accuracy and decision quality. Nothing executes yet.
Deliverable: Validation report
04
Promote and scale
Move the validated agent to production in one controlled action, then reuse its components for the next process.
Deliverable: Production deployment
Built in a conversation. Running in production.
At a global logistics customer, a business user described the process they wanted automated — in plain English, without touching a workflow builder. The skill that came out of that conversation now runs every week against real volume.
0+
Complex manifests processed each week by the resulting skill
0 min
Of conversation to build it — no builder, no code, no integration ticket
0%
Token cost of a saved skill versus the exploratory conversation behind it
The whole lifecycle
With MouRio vs. without
Not a feature list — the six places an enterprise AI programme usually stalls, and what each one looks like from either side.
With MouRio
Inside your network, next to your systems
Deployed in your own VPC, so prompts, documents and results never cross the perimeter. Agents call your systems locally — no egress round-trip and no inspection on every hop. Independent steps also execute in parallel rather than in sequence, so wall-clock time is the longest path, not the sum of every step.
One governed platform, inside your boundary
Without MouRio
Outside your perimeter, on someone else's estate
Every prompt and every retrieved document crosses your boundary to a vendor environment — a data-protection review, a residency question and a contract clause — and pays the round-trip and inspection cost on each hop.
A SaaS platform, plus whatever you build around it
With MouRio
Two surfaces, one for each audience
IT and platform teams own the plumbing — connections, credentials, which tools exist and who is allowed to call them. Business users work in natural language against tools that are already approved and scoped. Neither group is asked to do the other's job, and a useful conversation can be saved as a reusable skill.
One governed platform, inside your boundary
Without MouRio
The wall just moved down the hall
Describing an agent in plain English is easy now. Connecting it to a system of record still means APIs, bearer tokens and scopes — so the barrier shifted from “learn to code” to “learn to integrate”, and the person who understands the process still cannot ship one without a sprint.
A SaaS platform, plus whatever you build around it
With MouRio
Shadow mode before anything executes
The agent runs against real work and proposes alongside the existing process without acting. You measure its accuracy against what actually happened, then promote it when the numbers justify it.
One governed platform, inside your boundary
Without MouRio
Pilot, then hope
Validation is a spreadsheet of hand-checked samples. Because there is no way to run the agent alongside the real process without acting, confidence comes from anecdote rather than measurement.
A SaaS platform, plus whatever you build around it
With MouRio
Validated to live in one controlled action
Promote to production without re-engineering integrations or rewriting policy, and publish the same agent as an API, a web app, an MCP endpoint or a realtime voice channel — the same governed agent, four surfaces. Weeks, not quarters.
One governed platform, inside your boundary
Without MouRio
A second project to go live
Production means re-integrating, re-implementing the guardrails, and building the API or front end separately. The gap between a working demo and a live process is where most programmes stall.
A SaaS platform, plus whatever you build around it
With MouRio
One view of every agent in production
The Control Tower shows every run, the failing nodes, the escalations waiting on a human, and cost and latency attributed per agent — with any run replayable step by step.
One governed platform, inside your boundary
Without MouRio
Scattered across dashboards
Model spend in one console, application logs in another, failures reported by the users who hit them. Nobody can say what an agent costs, how often it fails, or who owns it.
A SaaS platform, plus whatever you build around it
With MouRio
A bill that does not move
A fixed annual subscription. Nothing metered — not per agent, per user, per query or per message — so the finance conversation happens once a year rather than every time adoption grows.
One governed platform, inside your boundary
Without MouRio
A bill that grows with success
Consumption pricing means the agents people actually use cost the most, so budgeting becomes forecasting adoption — and the platform's cost is only part of the number.
A SaaS platform, plus whatever you build around it
Compare
You are evaluating more than one platform
So we set out the differences ourselves — deployment, control, and how each one charges you — side by side, and leave the conclusion to you.
Questions from the review board
The things risk teams ask first
Inside your own tenant — that is the whole design. MouRio deploys into your cloud subscription, VPC or data centre, and data residency, encryption keys and infrastructure stay within your boundary. Nothing is transmitted to us. For defence, public sector and the most tightly regulated environments we also run fully disconnected, with no egress at all — which is a question most agent platforms cannot answer.
Bring us the process nobody wants to own.
The one with the exception queue, the spreadsheet nobody documents, and the person who is the only one who knows how it works. We will map it, show you where governed AI fits, and tell you honestly if it does not.