AI-Native Execution Layer

Conversational AI with governed execution, MCP control and full interaction traceability

IVR.Ai operates as the universal AI provider of IVR 5.0 AI, enabling users to interact through conversational prompts or traditional UI without altering system architecture. All AI-driven actions are validated, filtered and governed through controlled protocols, ensuring objective evidence and operational traceability.

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AI Capabilities

  • Conversational interaction via natural language prompts
  • Hybrid operation: UI and AI coexistence
  • Governed execution through Model Control Protocol (MCP)
  • Traceable AI interactions with timestamped logs
  • Integration with RAG and domain Workers

AI-Native Platform Architecture

IVR 5.0 AI was designed as an AI-native industrial platform. The AI layer is not an external add-on but an integrated operational mode capable of interacting with all infrastructure and domain Workers.

Users can choose between classical UI interaction through IVR.Client or conversational prompts processed by IVR.Ai, without duplicating business logic or bypassing architectural boundaries.

AI operates within the same governed infrastructure stack as all other modules.

Model Control Protocol (MCP) Governance

All AI-generated intentions are validated and filtered through the Model Control Protocol (MCP), implemented by IVR.Mcp. MCP acts as a semantic firewall, enforcing business rules, operational boundaries and authorization policies.

This mechanism ensures that no AI suggestion can trigger actions beyond predefined industrial constraints, transforming AI usage into a controlled and auditable process.

  • Intent validation before execution
  • Business rule enforcement
  • Permission verification via Identity
  • Audit logging of AI decisions

Retrieval-Augmented Generation (RAG)

IVR.Ai integrates with IVR.Rag to enable Retrieval-Augmented Generation (RAG), allowing the model to access structured industrial data and validated knowledge bases before generating responses.

This architecture reduces hallucinations, increases contextual accuracy and ensures that AI responses are grounded in traceable operational data.

AI responses are context-aware, data-grounded and infrastructure-governed.

Traceability and Audit of AI Interactions

Every AI interaction—including prompt input, interpreted intent, applied rules and execution outcome—is recorded with correlation identifiers and timestamps. Logs are integrated with OpsMonitoring for cross-service visibility.

This end-to-end traceability enables investigation, compliance validation and measurable governance of AI-driven operations within industrial environments.

AI becomes a transparent, auditable and controllable operational layer.

Scalability and Distributed Deployment

IVR.Ai operates as an independent Web API service, containerized and deployable in distributed environments. It communicates with IVR.Server via HTTP and interacts with Workers through controlled APIs and message queues.

This separation ensures horizontal scalability, workload isolation and alignment with Clean Architecture, DDD principles and container-based execution.

AI capabilities scale independently while remaining governed by the core infrastructure.