The infrastructure that
makes 94% autonomy
possible.

The PLRX Agentic Execution Platform decomposes every complex workflow across a team of specialist AI agents — each owning a bounded domain of responsibility. An orchestrating agent drives the overall mission lifecycle and delegates work to specialists via the A2A protocol. Specialists execute in parallel where the workflow permits and signal the orchestrator on completion.

Each specialist agent is an independently deployable service. It owns its own durable workflow instance, its own named task queue, and its own isolated data schema. There is no shared state between agents. There is no cross-agent coupling. An orchestrator never reads a specialist's data directly — information moves exclusively through A2A task payloads.

This means each agent scales independently, deploys independently, and fails independently. A specialist restart does not affect the orchestrator's workflow state. The platform does not require all agents to be running for any individual one to operate. Agents can be licensed and deployed standalone, or composed into coordinated fleets.

What this means for your operations: a workflow spanning your EHR, a payer, a clearinghouse, and a fulfilment system is coordinated by a fleet of specialists — each running independently, each accountable for its own domain. Your workflow never bottlenecks on a single agent, and no single failure stops the mission.

Every agent mission runs inside the PLRX Durable State Machine. Workflow state is persisted continuously — not in volatile memory, not in a database that can be left in an inconsistent state, but in an append-only event log that survives any failure. When a system restarts, the workflow replays deterministically from the log and resumes exactly where it stopped.

This durability is not optional and not configurable. It is the foundation of the platform. Missions that wait on a provider document for three weeks, a payer callback for two days, or a supplier confirmation for an hour all suspend and resume without losing a single byte of state.

Strict idempotency keys on every side-effecting operation — every email sent, every API call made, every record written — guarantee exactly-once execution semantics regardless of how many times an activity is retried. No duplicate emails. No duplicate submissions. No double billing. No duplicate API calls. Ever.

What this means for your operations: a mission waiting three weeks for a physician's signature resumes exactly where it paused — no data lost, no step repeated, no external system called twice. Your workflow runs to completion regardless of how long the real world takes to respond.

The PLRX Agentic AI Execution Platform is built on two open standards for machine-to-machine and human-to-machine coordination. Neither is proprietary. Both are inspectable. Both are composable with any system that implements them.

A2A (Agent-to-Agent) is an open JSON-RPC 2.0 protocol for machine-to-machine task delegation, initiated by Google and backed by industry partners. It defines how agents advertise their capabilities, how tasks are submitted and tracked, and how status is communicated. Every PLRX agent is a fully compliant A2A server. Any A2A-compliant client — inside or outside the platform — can call any PLRX agent by name.

MCP (Model Context Protocol) is an open standard by Anthropic that defines how AI clients discover and invoke tools, read resources, and receive streaming responses from external servers. The PLRX MCP Server exposes the full platform as a set of MCP tools — one per agent workflow. Any MCP-compatible AI client can invoke a complete PLRX mission, track its status, and receive real-time updates without any knowledge of the underlying agents, protocols, or systems. Connect once. Access everything.

What this means for your operations: the AI tools your team already uses can trigger and monitor full PLRX missions without any custom integration work. No new interfaces to learn. No proprietary SDKs to install. And because both protocols are open standards, there is no lock-in — ever.

PLRX runs on a shared environment by default — multi-tenant infrastructure with strict data isolation at every layer. For customers in regulated industries or with enterprise security requirements, a dedicated environment is available: a separate Kubernetes cluster with no shared runtime and no shared data plane. Cross-tenant data access is structurally impossible in both models — isolation is architectural, not a policy.

Every environment is provisioned on demand via infrastructure-as-code. The deployment is Kubernetes-native on AWS. Customers who require specific region placement get exactly that. The platform runs inside Kubernetes pods, not inside any proprietary managed services.

All data in transit is encrypted end-to-end. All PHI and sensitive fields are encrypted at rest via field-level converters before they touch persistent storage. Every AI prompt sent to any model — its full text, model name, token counts, timestamp, and workflow context — is captured in append-only WORM audit logs that cannot be modified or deleted. HIPAA compliance is not a feature added on top. It is the baseline.

What this means for your operations: your IT and compliance teams get a platform that passes security review by architecture — not by policy. No BAA negotiation delays. No security questionnaire surprises. No remediation required after deployment.