Propose useful knowledge
Bring source material, operational feedback and corrections into a review process. Treat new information as a proposal until an owner checks it.
How Reimea works
From one agent action to agents at scale.
How an agent action runs, what a single request looks like end to end, where Reimea is deployed, who it is for and where it is heading. For the product range, see all products.
Why now
Agents are arriving faster than the controls around them.
The question for regulated organisations has moved on from whether to use AI agents. It is now who answers for what an agent did, and whether you can prove it afterwards.
33%
of enterprise software applications are expected to include agentic AI by 2028.
15%
of day-to-day work decisions are expected to be made autonomously by agents by 2028.
40%+
of agentic AI projects are expected to be cancelled by the end of 2027, partly because of weak risk controls.
Source: Gartner predictions, June 2025, as reported by SD Times.
The models are not what holds these projects back. What holds them back is identity, policy, approval and evidence. That is the work a CISO, a SIRO or a clinical safety officer has to sign.
Reimea starts there. We build the control layer first, then put agents to work inside it. You can expand what agents do without losing sight of who is accountable.
Controlled AI learning
Better knowledge.
Controlled change.
Give agents a way to use improving knowledge while keeping ownership, approval and publication in human hands. Decide what changes, who reviews it and where the approved version may be used.
Make ownership explicit
Review the wording, evidence, intended audience and service scope. A named person decides whether staged content is ready to publish.
Control the revision
Keep source references, versions and review dates visible. Revised or deprecated content needs a new lifecycle decision before reuse.
Use knowledge within scope
Retrieve eligible references for the permitted module and service. People can inspect the evidence behind a suggestion and decide the next action.
Govern what agents know
Knowledge Control manages the content lifecycle. Meridian Knowledge retrieves relevant passages and makes sources inspectable. The concept graph helps explain how sources, concepts, controls and products connect.
Keep learning accountable
This approach improves the governed knowledge agents can retrieve. Models do not retrain themselves or change their own permissions. Operational feedback still needs an agreed review process; module-specific workflows and deployment checks apply.
How an agent action runs
Six steps. No shortcuts.
- 1
Listen
A call, request or question arrives. The agent captures it against a versioned script.
- 2
Draft
The agent drafts a capture, suggestion or answer, citing its sources.
- 3
Check
Identity, entitlements and model policy are checked at the gateway before anything is used.
- 4
Approve
A named handler reviews the draft, then accepts, edits or rejects it.
- 5
Act
Only then is the handover made, the ticket assigned or the record updated.
- 6
Record
Application audit events support review; coverage and durable storage need verification.
A concrete example
See one request move through the work.
Capture the request, inspect an AI draft, review its source and make a human decision. The guided example uses fictional IT service data.
No live calls or model requests. No patient records.
Explore the 90-second walkthrough
Cloud deployment / Azure & AWS
Your cloud.
Your governance.
Reimea’s deployment direction covers Microsoft Azure and Amazon Web Services (AWS), giving organisations a choice of cloud environment for their agent control platform.
Control across either environment
Agent permissions, governed knowledge, human review and evidence remain the platform’s focus. The selected cloud services, integrations and validation must match the customer’s requirements.
AWS deployment is planned. The current source-reviewed evidence covers the Azure design; cloud-specific release and deployment verification will be agreed for each environment.
The Reimea vision
From assisted work to agents at scale, without losing the thread.
Trust in agents is earned in stages. Each stage widens what agents may do on their own, and the same control layer stays underneath.
Assist
Agents listen, draft and suggest. A person approves every action before it reaches a system.
- Voice capture and handover
- Suggested ticket assignment
- Cited knowledge answers
Delegate
Agents act on their own inside a policy boundary you set. People handle the exceptions and review samples.
- Approval by exception, set per action type
- Confidence and coverage thresholds
- Bring-your-own agents through the gateway
Orchestrate
Agents work across teams and organisations, handing work to each other with provenance and consent intact.
- Agent-to-agent handover, fully audited
- Source-attributed records through Exchange
- One accountable view across a care system
Horizons 2 and 3 describe direction, not shipped features. We will publish each capability with its evidence when it is built.
Who it is for
Built where mistakes are expensive.
Reimea is designed for organisations whose buyers include a CISO, a SIRO or a clinical safety officer, and who need to answer to a regulator.
Health and care
Out-of-hours, urgent care and NHS-commissioned services. Voice capture, reviewed handover and service desks, with intended-use and assurance work scoped before deployment.
Financial services
Contact centres and operations teams where every decision needs an owner, an audit trail and a model-risk story.
Multi-site operations
Shared service desks, IT and estates teams that want agents doing the routine work while working inside a customer-specific cloud environment.
Put agents to work. Keep the controls.
A 45-minute briefing for your technology, security and governance leads. We cover the control layer, Azure or AWS deployment planning and an honest view of what is ready.