> ## Documentation Index > Fetch the complete documentation index at: https://docs.alysio.ai/llms.txt > Use this file to discover all available pages before exploring further. # Custom Agents > Create custom AI Revenue Agents ## Custom Agents Custom Agents allow organizations to design AI Revenue Agents tailored to their unique revenue operations workflows. While Agent Templates provide preconfigured starting points, Custom Agents enable teams to build automation that reflects their specific pipeline processes, account strategies, and operational policies. Revenue organizations often operate with distinct sales motions, segmentation models, and internal processes. Custom Agents allow administrators and revenue operations teams to define automation that aligns with these operational realities. Using the Agent Builder, Custom Agents can monitor operational signals, evaluate defined conditions, and execute workflows across connected revenue systems. *** ## Definition **Custom Agents** are AI Revenue Agents created from scratch within the Agent Builder to automate organization-specific revenue workflows. Unlike templates, which provide predefined structures, Custom Agents allow administrators to fully define: Signal triggers\ Execution conditions\ Operational logic\ Workflow actions\ System integrations used during execution This flexibility allows organizations to build automation that precisely matches their internal revenue processes. *** ## When to Use Custom Agents Custom Agents are most useful when organizations need to automate workflows that are not covered by standard templates. Examples include: Monitoring specialized sales stages unique to the organization\ Tracking engagement activity across specific stakeholder groups\ Automating workflows tied to internal approval processes\ Responding to signals from proprietary data sources\ Coordinating actions across multiple internal systems These scenarios require tailored automation logic that reflects the organization’s operational structure. *** ## Designing a Custom Agent Creating a Custom Agent involves defining the operational logic that determines how the agent monitors signals and performs actions. The configuration process typically includes several components. ### Agent Objective The first step is defining the operational goal of the agent. Examples include: Monitoring high-value enterprise opportunities\ Identifying accounts with declining multi-threaded engagement\ Detecting early churn indicators for key customers\ Automating internal deal review preparation The objective determines the signals and workflows associated with the agent. *** ### Signal Triggers Custom Agents rely on signals generated by the Signals Engine to determine when automation should occur. Common signals include: Deal stagnation\ Engagement decline\ Pipeline velocity slowdown\ Renewal milestone signals\ Account-level intelligence signals Administrators can select one or more signals that activate the agent’s workflow. *** ### Execution Conditions Execution conditions define the operational context required for the workflow to run. Examples include: Deal size thresholds\ Account segmentation filters\ Opportunity stage requirements\ Customer lifecycle stage conditions\ Time-based triggers such as renewal windows These conditions ensure automation runs only in appropriate scenarios. *** ### Workflow Actions Once trigger conditions and execution logic are satisfied, the agent executes a defined set of operational actions. Examples include: Creating CRM tasks for account owners\ Updating opportunity fields in the CRM system\ Sending alerts to sales managers\ Posting summaries to Slack channels\ Generating executive meeting briefs These actions are executed through the platform’s Execution Engine. *** ### System Integrations Custom Agents may interact with multiple systems connected to the Alysio platform. Examples include: CRM platforms such as Salesforce and HubSpot\ Collaboration platforms such as Slack\ Communication tools such as email and calendar systems\ External intelligence providers such as ZoomInfo These integrations allow agents to coordinate workflows across the revenue stack. *** ## Custom Agent Creation Process Creating a Custom Agent through the Agent Builder typically follows several steps. ### Step 1: Define the Operational Objective Administrators identify the revenue scenario the agent should monitor or automate. *** ### Step 2: Select Signal Triggers The administrator selects the signals that should activate the workflow. These signals are detected by the Signals Engine based on operational data across connected systems. *** ### Step 3: Configure Execution Conditions Operational conditions are defined to ensure that automation runs only when the appropriate context exists. *** ### Step 4: Define Workflow Actions The administrator specifies the operational actions the agent should perform when triggered. *** ### Step 5: Deploy the Agent Once configuration is complete, the Custom Agent is deployed within the workspace. After deployment, the agent continuously monitors operational signals and executes workflows when the defined conditions occur. Administrators can review agent activity through the platform’s operational logs. *** ## Example Custom Agent A revenue operations team creates a Custom Agent designed to monitor enterprise opportunities showing declining engagement. Signal trigger\ Engagement decline detected by the Signals Engine. Execution conditions\ Opportunity value greater than \$250,000\ Opportunity stage equals Negotiation. Workflow actions\ Create a follow-up task for the account owner\ Notify the regional sales director through Slack\ Generate an executive pipeline review summary. This automation ensures that high-value opportunities receive attention when engagement begins to decline. *** ## Operational Impact Custom Agents allow organizations to automate workflows that reflect their specific operational strategies. Organizations commonly experience benefits such as: Greater flexibility in automation design Improved alignment between automation and internal revenue processes Faster response to operational signals affecting critical deals Reduced reliance on manual monitoring and administrative tasks By tailoring automation to their specific workflows, organizations can scale revenue operations while maintaining operational control. *** ## Platform Data Flow Custom Agents operate through several core components of the Alysio platform. Connected Revenue Systems\ ↓\ Alysio Signals Engine\ ↓\ Custom Agent Configuration\ ↓\ AI Revenue Agents\ ↓\ Execution Engine\ ↓\ Operational Actions Across Systems Diagram Alt Text Diagram illustrating how custom-configured AI Revenue Agents monitor operational signals, evaluate execution conditions, and perform automated workflows across connected revenue systems. *** ## Summary Custom Agents allow organizations to design automation tailored to their unique revenue operations workflows. By defining signal triggers, execution conditions, and workflow actions, administrators can create AI Revenue Agents that continuously monitor operational activity and respond automatically to important events. This flexibility enables organizations to automate complex revenue processes while maintaining control over how workflows operate across their revenue stack.