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Automated Executions represent how AI systems perform structured, repeatable actions within a project. They are accessed through the Automation Panel and are designed to execute workflows based on data, context, and predefined logic.

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What are Automated Executions?

Automated Executions are predefined workflows powered by AI agents. They allow the system to:
  • Process structured data
  • Apply multi-agent reasoning
  • Execute actions across integrations
  • Generate consistent outputs
Each execution is tied to a specific use case defined by the selected AI template.

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Execution Model

Automated Executions operate as: Data → Agents → Decision → Action
  • Data is processed through pipelines
  • Agents analyze and segment information
  • Decisions are generated based on context
  • Actions are executed through integrations

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Example: Customer Intelligence

Within the Customer Intelligence system, executions are structured around customer data. Typical execution flow:

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Customer Clustering

  • Users are grouped into segments based on behavior and attributes
  • Clusters are continuously updated from pipeline data

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Marketing Strategy Generation

  • Each cluster is analyzed independently
  • Targeting strategies are generated

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Campaign & Template Execution

  • Email or campaign templates are generated per cluster
  • Campaigns can be created and executed through integrations
This creates a full flow: Customer Data → Clusters → Strategy → Campaign Execution

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Execution Units

Automated Executions are organized into execution units. Each unit represents a specific task, such as:
  • Segmentation
  • Campaign generation
  • Template creation
  • Action execution
These units are combined to form complete workflows.

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Interaction Model

Users interact with Automated Executions through the Automation Panel. They can:
  • Trigger executions
  • Monitor progress
  • Review outputs
  • Re-run workflows
All executions are deterministic and tied to system configuration.

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Integration with System

Automated Executions connect all major system components:
  • Pipelines → Provide structured data
  • Context System → Adds intelligence and grounding
  • AI Agents → Perform reasoning and decision-making
  • Integrations → Execute actions externally

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Scope & Control

  • Executions are scoped to projects
  • Defined by the selected AI template
  • Controlled by roles and permissions
Each execution runs within a bounded system environment.

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Positioning

Automated Executions are the action layer of Avigrah. They enable the system to move beyond analysis and perform:
  • Structured decision-making
  • Workflow execution
  • Real-world actions through integrations