The worker runtime implements routing, consensus, remediation, drift-aware policy, and cost guardrails. The public site is informational; live runtime data still requires a protected API path.
Modern AI applications depend on proprietary models that change behavior silently over time.
Without a governance layer, these issues are detected only after production failures occur.
Sitting between your application and provider APIs, PlurisUnum orchestrates workloads down to the prompt level within a controlled launch boundary.
"PlurisUnum is designed to be the orchestration layer between applications and the expanding AI ecosystem.
Rather than relying on a single model, applications can leverage multiple forms of intelligence simultaneously."
Examples include Life OS, RemedyMatrix, Tax AI, and other applications built on the platform.
Handles routing, verification, arbitration, consensus intelligence, and guardrails.
External model providers such as OpenAI, Gemini, Grok, Anthropic, and future providers.
This section separates live runtime signals, offline diagnostics, and illustrative examples so the public site never asks visitors to guess what is current truth.
Public Pages needs a protected worker connection before observability and guardrail metrics can be shown as live truth.
Simulation and deterministic harness results remain useful evidence, but they are not the same thing as live traffic telemetry.
Any sample metric shown below is presented as an example shape, not a current public KPI.
Percentage of orchestration runs that produced a verified successful outcome.
Percentage of failed first-pass executions successfully recovered via consensus.
Average execution cost required to produce a verified successful outcome.
Composite signal indicating platform decision quality is improving over time.
Detect model degradation before your system breaks. The sample below illustrates how drift findings may be presented; it is not live operational telemetry.
Test AI orchestration policies entirely offline. The sample below is a static example of how an offline simulation result can be communicated; it is not live operational data.
Integrate the protected worker runtime, not the public Pages site. The contract below is infrastructure-only and aligned to the supported execution path.
// Minimal real integration shape. Use a protected worker host and a signed identity token. const response = await fetch('https://<protected-worker-host>/v1/intelligence/execute', { method: 'POST', headers: { 'Authorization': 'Bearer <signed-identity-token>' }, body: JSON.stringify({ task: 'Analyze this schema.', input: 'schema contents here', intent: 'verification-weighted', constraints: { providers: ['openai', 'google'] } }) }); // Advanced orchestration remains infrastructure-driven. // Intent and provider constraints stay declarative at the request boundary.
Future provider names should not be treated as live support until the worker contract and verification evidence are both present.
Integrate PlurisUnum through the protected worker runtime. The public Pages site is informational, and the same-origin `/api` path should be treated as a proxy surface, not a public unauthenticated runtime.
// Minimal supported request payload { "task": "Explain blockchain security", "input": "Use a concise infrastructure-focused answer.", "intent": "consensus" } // Canonical response fields shown here as an example shape { "result": "Blockchain security relies on cryptographic hashing...", "selected_strategy": "triple_consensus", "provider_path": ["openai:gpt-4o-mini", "google:gemini-1.5-pro"], "estimated_or_actual_cost": 0.005 }
Use a truth-first control plane that makes launch stage, live runtime state, and protected diagnostics explicit.
Open Operator Console