Our platform
RealRelay.ai
A platform for building, governing and deploying AI agents. It reaches several third-party models through one route, picks between them for each task, and runs on infrastructure you are permitted to use.
Capabilities
What the platform does that a model on its own cannot.
Every domain we build inherits these, and so does every domain a partner builds with us.
Governance inside the runtime
Policy, identity and audit sit in the execution path, not in a reporting layer added afterwards. What an agent may reach, who authorised it, which model answered and what was done are all recorded as it happens.
Routing between models
Not every task needs the most capable model. Requests go to a model chosen on the merits of the task, weighing speed, cost and capability, and following your rules on what may leave your environment at all.
Assembly without code
Describe what an agent should do and the platform helps you structure it, connect the tools it needs and check it before it runs. The people who understand the workflow build the agent, and that is what lets this move past a pilot.
Security inside the platform
A validation agent runs against the agents you build, continuously and within a scope you set. It returns risk ratings with evidence and remediation steps, not a report at the end of a project. How that works.
One route to many models
Separate contracts with separate providers, each with its own terms and invoice, become one route with one set of controls. You can change providers without rebuilding what sits above them.
Architecture
How the platform is put together.
The experience layer is what your people work in, the domains carry the sector expertise, and the core supports both. That shared core is why a new domain takes months to stand up instead of 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. It runs once before release, then goes stale while the agent keeps changing.
RealRelay.ai carries the validation inside the platform. An agent is built and tested in the same environment, so the checks keep pace with the agent as it changes.
Testing that does not stop
An autonomous validation agent probes the agents you build, continuously and not just at a single gate before release. An agent that changes on Tuesday is tested 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 supporting evidence and what to do about it.
A loop that closes
Find, fix, re-test. Because development and verification sit in the same environment, a finding becomes a fix and the fix is confirmed, wherever you run: our cloud, your infrastructure or fully disconnected, with your own keys and local models.
We would rather be clear about this. 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, three ways to run it.
Which one you run should follow what your regulator and your board require, not what a vendor happens to support.
Fastest to value
Run and maintained by us, with regional residency options. This is where most enterprise teams start.
- 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 leaves the environment.
- 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 that somebody set deliberately. These are the four parts of those limits.
Scoped permissions
An agent gets the tools and data its task requires and nothing next to it. Scope is declared before deployment, not 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 checked against policy before they run. The same gate applies to a student's first assistant and to 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 it looks like handled well.