Our platform
RealRelay.ai
A platform for creating, governing and deploying AI agents. It reaches several third-party models through one route, selects between them per task, and runs on infrastructure you are permitted to use.
Capabilities
What the platform does that a model alone does not.
Every domain we build inherits these, and so does every domain a partner builds with us.
Routing between models
The most capable model is not required for every task. Requests are directed to a model chosen on the merits of the task, weighing speed, cost and capability, and observing rules about what may leave your environment at all.
Assembly without code
Describe what an agent should do and the platform helps structure it, connect the tools it needs and check it before it runs. The people who understand the workflow build the agent, which is what allows this to move beyond a pilot.
Governance inside the runtime
Policy, identity and audit are not a reporting layer added afterwards. They sit in the execution path: what an agent may reach, who authorised it, which model answered and what was done, recorded as it happens.
Security inside the platform
A validation agent runs against the agents you build, continuously and within a scope you set, returning risk ratings with evidence and remediation rather than a report at the end of a project. How that works.
One route to many models
Separate arrangements with separate providers, each with its own terms and invoice, become one route with one set of controls. Providers can be changed without rebuilding what sits above them.
Architecture
How the platform is put together.
The experience layer is what your people touch, the domains carry the expertise, and the core is what both rest on. That core is also the reason a new domain takes months rather than years.
The platform is engineered and operated with our partner CWG Innovations, and every domain runs on the same architecture. More at cwgsg.ai.
Security, built in
The platform tests the agents you build on it.
On most platforms, building an agent and checking whether it is safe are two separate purchases. Security testing arrives as a tool you bolt on afterwards, runs once before release, and then goes stale while the agent keeps changing.
RealRelay.ai carries the validation inside it. An agent is built and examined in the same environment, so the check keeps pace with the thing being checked.
Testing that does not stop
An autonomous validation agent probes the agents you build, continuously rather than at a single gate before release. An agent that changes on Tuesday is examined on Tuesday.
Adversarial, inside your scope
Within the boundary you authorise, it reasons the way an attacker would to surface real exposures, and reports each one with a risk rating, the evidence behind it and what to do about it.
A loop that closes
Find, fix, re-test. Because development and verification sit in one environment, a finding becomes a fix and the fix is confirmed, wherever you run: our cloud, your infrastructure or disconnected, with your own keys and local models.
We are precise about our posture. Paradise Matrix does not currently hold formal security certifications, and we do not describe ourselves as certified for anything we have not earned. Security and compliance characteristics vary by deployment tier and are set out in your agreement with us.
Deployment
The same platform in three postures.
Which one you run should follow what your regulator and your board require, not what a vendor is able to support.
Fastest to value
Run and maintained by us, with regional residency options. The usual starting point for enterprise teams.
- Managed upgrades
- Regional residency options
- Elastic capacity
Inside your perimeter
The platform runs on your own infrastructure, integrated with your identity systems and with key management under your control.
- Runs inside your network
- Keys held by you
- Integrates with existing identity
No outbound path
For classified, defence and critical infrastructure settings. Open-weight models are served locally and nothing is sent outward.
- Models served locally
- No outbound telemetry
- Offline update process
Security, sovereignty and compliance capabilities vary by product, release stage and deployment tier, and are governed by your agreement with us.
Governance and assurance
How we keep an agent inside its boundary.
Every agent works inside limits somebody set deliberately. These are the four parts of them.
Scoped permissions
An agent receives the tools and data its task requires and nothing adjacent. Scope is declared before deployment rather than discovered afterwards.
Human checkpoints
Consequential actions stop for approval. Which actions those are is your decision, set per agent and per environment.
A complete record
Prompt, plan, tool call, model selected, output and approver, held in sequence and exportable for review months later.
Checks before release
New agents are evaluated against policy before they run, a gate that applies equally to a student's first assistant and a production security agent.
Start with one workflow.
The platform runs today across cybersecurity, education and fintech. Tell us which workflow matters most to you and we will show you what good looks like on it.