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AI agents in Elementum are conversational assistants tied to your apps. They interpret what people ask for, use tools to work with records and automations, and reach users on channels such as Microsoft Teams or phone calls. First-line support is a typical starting point; the same patterns apply to onboarding, sales, or any process where a guided conversation speeds up routine work. For creating an agent, adding it to an app, and configuring models and instructions in the UI, see Building Agents.

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Tools

Agents use tools to take action during conversations — creating or updating records, running searches, triggering automations, delegating to sub-agents, or calling external services through MCP. Each tool has a name, description, permissions mode (Run as publisher, Run as current user, or Run as service account), and type-specific configuration. For configuration steps and field-level details for each tool type, see Building Agents — Configure Agent Tools. Available tool types:
  • Create Record — Create new records in a specified App, Element, or Task
  • Record Search — Search for existing records based on a query (returns up to 100 results)
  • Update Record — Update fields on an existing record identified by record ID
  • AI Search Records — Semantic search using AI to retrieve records based on natural language
  • Run Automation — Execute an automation with an On-Demand trigger, passing input and receiving output values
  • Run Agent — Delegate a task to a sub-agent in a new conversation
  • MCP — Connect to an external MCP server and invoke its tools
  • Skills — Dynamically discover and run reusable Skills at runtime (no manual tool setup required)

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Deploying Agents

Once configured, agents can run in several contexts:

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External Agents via App Intelligence

In addition to creating and managing internal agents, Elementum supports integration with external agents configured at the App level through Intelligence settings. You can connect specialized AI capabilities from external providers such as Snowflake Cortex and AWS Bedrock while keeping data access governed by your provider configuration.

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External Agent Configuration

External agents are configured at the App level through Intelligence settings, not centrally. This approach ensures:
  • App-Specific Context: Agents access only the data relevant to their App
  • Scoped Permissions: Security controlled through AI Provider credentials
  • Independent Configuration: Each App can configure agents according to its needs
  • Flexible Deployment: Different Apps can select different providers and agents
Key Concepts:
  • Native agents: Built and hosted in Elementum
  • Managed agents: External agents (for example Cortex or Bedrock) integrated through App Intelligence
  • App Intelligence: Configuration area where external agents are discovered and connected
  • AI Provider: Provider configured with appropriate credentials for agent discovery and invocation

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Snowflake Cortex Agents Integration

Snowflake Cortex Agents are a common choice for external agents. Cortex Agents run on your Snowflake data warehouse so automation can use warehouse data without copying it out of Snowflake. Configuration Steps:
  1. Navigate to App Intelligence:
    • Go to the App where you want to use Cortex Agents
    • Under App Admin, select Intelligence
  2. Add External Agent:
    • Click “Add Agent” button
    • Select “External” as the agent type
    • Choose a Snowflake AI Provider from the dropdown
  3. Discover and Select:
    • Elementum queries Snowflake Cortex REST API through the provider
    • Available Cortex Agents are displayed
    • Select the agent you want to use
    • Configure agent settings and save
  4. Use in Automations:
    • When configuring automation actions
    • Select the external agent from available agents
    • Configure input parameters and output handling
    • Set timeout and error handling options
Benefits of Snowflake Cortex Agents:
  • Data Security: AI runs on your data warehouse—data never leaves your environment
  • Performance: Direct access to data eliminates transfer latency
  • Compliance: Maintains data governance and regulatory requirements
  • Scalability: Leverages Snowflake’s compute infrastructure
Example Use Case:
  • Automated Data Analysis: When a monthly report is requested, an automation invokes a Cortex Agent to analyze sales trends, generate insights in natural language, and populate the report automatically—all while the data remains secure in Snowflake.

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AWS Bedrock Agents Integration

AWS Bedrock Agents use Amazon foundation models and can include action groups, knowledge bases, and guardrails. They integrate with your AWS infrastructure when invoked through a configured Bedrock AI Provider. Configuration Steps:
  1. Navigate to App Intelligence:
    • Go to the App where you want to use Bedrock Agents
    • Under App Admin, select Intelligence
  2. Add External Agent:
    • Click “Add Agent” button
    • Select “External” as the agent type
    • Choose a Bedrock AI Provider from the dropdown
  3. Connect Agent:
    • Enter the Agent Alias ARN from your AWS Bedrock configuration
    • Elementum validates the connection through the provider
    • Configure agent settings and save
  4. Use in Automations:
    • When configuring automation actions
    • Select the external Bedrock agent from available agents
    • Configure input parameters and output handling
    • Set timeout and error handling options
Benefits of AWS Bedrock Agents:
  • AWS Ecosystem Integration: Native integration with AWS services, Lambda functions, and S3
  • Knowledge Bases: Connect agents to enterprise knowledge stored in S3 or other AWS data sources
  • Action Groups: Define custom actions using Lambda functions for complex business logic
Example Use Case:
  • Customer Service Automation: When a support request is created, an automation invokes a Bedrock Agent that accesses knowledge bases, retrieves customer history, and provides contextual responses—all within your AWS environment.

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Agent Discovery and Management

External agents are discovered through their respective AI Providers: Snowflake Cortex Agents:
  1. App Intelligence prompts for Snowflake AI Provider selection
  2. Selected provider’s CloudLink authenticates with Snowflake
  3. Queries Snowflake Cortex REST API for available agents
  4. Retrieves agent metadata (capabilities, schemas, permissions)
  5. Displays available agents for selection
  6. Registers selected agents for use in App automations
AWS Bedrock Agents:
  1. App Intelligence prompts for Bedrock AI Provider selection
  2. Selected provider authenticates with AWS using configured credentials
  3. User provides the Agent Alias ARN for the target agent
  4. Elementum validates connectivity via the InvokeAgent API
  5. Agent is registered for use in App automations
Management:
  • Per-App Configuration: Each App configures its own external agents
  • Provider-Based Access: Apps select from configured AI Providers
  • Intelligence Dashboard: View configured external agents in App Intelligence
  • Provider Dependency: Agent availability depends on provider health
  • Centralized Visibility: View all agents across Apps in Agent Orchestration Center

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Technical Integration

External agents integrate with Elementum automations through App Intelligence. The flow varies slightly by provider type: Snowflake Cortex Integration: AWS Bedrock Integration: Security Model:
  • Snowflake: Authentication via CloudLink credentials, permissions enforced at Snowflake level, data governed by Snowflake RBAC
  • AWS Bedrock: Authentication via IAM credentials (Access Key/Secret Key), permissions enforced by IAM policies, data governed by AWS IAM
  • Both: All interactions audited, app-level isolation with provider-based access controls
For detailed setup instructions, see:

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Agent-to-Agent Protocol (A2A)

Elementum supports the Agent-to-Agent (A2A) protocol, an open standard that enables external systems to communicate with Elementum agents programmatically. This allows other AI agents, automation platforms, or custom applications to interact with your Elementum agents as remote collaborators. For the full A2A reference — architecture, authentication, Agent Cards, JSON-RPC examples, streaming, task states, and multi-turn conversations — see Agent Architecture & A2A Protocol.

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Next Steps