Turn data + AI outputs into action.

The Execution Layer is Layer 3 of the 5-layer Rayven Platform stack. It is the action engine of the platform — responsible for automating workflows, deploying and running AI models, firing alerts, evaluating business rules, processing complex events, and triggering updates to connected systems based on real-time data conditions. Everything the Data Layer produces becomes actionable through the Execution Layer.

The Execution Layer supports a wide range of automation types: alert-driven notifications (send a message when a value exceeds a threshold), workflow automation (multi-step processes with branches and approvals), AI-driven actions (run a model and act on its output), scheduled tasks (run something at a defined time), event-based triggers (respond to patterns across multiple data streams), and external system updates (write back to ERP, CMMS, cloud platforms, or any API-connected system).

The alert engine evaluates conditions against incoming data in real time. Conditions can be based on threshold breaches, rate-of-change, statistical anomalies, or custom expressions. When a condition is met, alerts are delivered via email, SMS, Microsoft Teams, Slack, PagerDuty, webhook, or in-platform notification — with configurable escalation, acknowledgement tracking, and snooze logic.

Yes. Rayven allows you to deploy machine learning models and AI functions directly into the platform's workflow environment. Models can be called as a step within an automation — receiving data inputs and producing outputs that drive subsequent actions. Rayven supports models built externally (imported via API or file) as well as those trained within the platform. Model outputs are logged, versioned, and auditable.

Workflows in the Execution Layer can be triggered in four ways: by a data condition (a value or pattern in the Data Layer), by an external event (a webhook or API call from an external system), on a schedule (a defined time or interval), or manually (by an authorised user via the platform or API). Multiple trigger types can be combined for complex orchestration scenarios.

Yes. The Execution Layer includes a complex event processing (CEP) engine that can detect patterns across multiple data streams simultaneously — for example, identifying that three separate sensor readings have moved in a correlated way over a 10-minute window. This enables use cases like predictive maintenance triggering, safety interlock automation, and multi-condition alert suppression.

Yes. Workflow actions can write to any system connected to the Rayven Integration Layer — including ERP systems, CMMS platforms, cloud APIs, databases, messaging services, and IoT actuators. Rayven also exposes a webhook action type so workflows can trigger any HTTP-capable external service. All outbound actions are logged and can be retried or escalated on failure.

All rules, workflows, and automation logic in the Execution Layer are managed centrally in the Rayven admin interface. Changes are versioned with author, timestamp, and description. Activation, deactivation, and modification of any automation creates an audit log entry. Teams can maintain staging and production environments with controlled promotion of changes.

Execution Layer workflows include configurable failure handling: retry with backoff, alternative action paths, escalation alerts, and dead-letter queuing for failed actions pending manual review. If a connected system is unavailable, the workflow can pause and retry, alert a human for intervention, or take a fallback action — depending on the criticality of the process.

The Execution Layer sits between the Data Layer (Layer 2) and the Presentation Layer (Layer 4). It consumes real-time and stored data from the Data Layer to drive automated actions, and produces outputs — updated records, alerts, model results, system writes — that are reflected in dashboards and reports in the Presentation Layer. It is also the layer that pushes data back out to connected external systems, closing the operational loop.