> ## 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. # Signals Engine Setup > Configure signal detection across the revenue stack ## Signals Engine Setup Understood. Here is the correctly formatted version using ## headers and section separators, matching the structure you’ve been using across the docs. *** ## Intelligence Engine ## Signals Engine Setup The Signals Engine Setup process allows organizations to configure how the Alysio platform detects operational signals across the revenue stack. Signals are patterns or events identified within operational data that indicate changes in pipeline health, account engagement, deal progression, or forecast conditions. Modern revenue organizations generate large volumes of operational data across CRM systems, engagement platforms, communication tools, and intelligence providers. While this data contains valuable insights, identifying meaningful operational patterns manually requires extensive reporting and cross-system analysis. The Alysio Signals Engine enables organizations to automatically detect these patterns by continuously analyzing activity across connected systems and surfacing signals that may influence revenue outcomes. *** ## Definition The Signals Engine is a core component of the Alysio Intelligence Engine responsible for detecting operational signals across connected revenue systems. The engine evaluates activity across the revenue stack to identify meaningful patterns such as stalled opportunities, declining engagement, pipeline coverage gaps, and upcoming renewal milestones. When a configured condition is met, the platform generates a signal event that can be surfaced through conversational insights, alerts, or automated workflows coordinated by AI Revenue Agents. *** ## Purpose of Signals Engine Setup The purpose of configuring the Signals Engine is to ensure that important operational changes are detected consistently across the revenue stack. Signals provide early visibility into conditions that may influence deal progression, customer engagement, or forecast reliability. Examples of questions signals help answer include: Which opportunities are currently stalled in the pipeline? Where has customer engagement declined recently? Which deals may be at risk of slipping past their close date? Which accounts are showing signals of expansion or growth potential? Where does pipeline coverage fall below expected targets? By detecting these conditions automatically, revenue teams can respond to operational changes before they affect forecast outcomes. *** ## Core Components of the Signals Engine Signals Engine configuration involves defining how signals are detected, evaluated, and surfaced across the platform. ### Signal Definitions Signal definitions specify the operational conditions that trigger a signal. Examples include: Opportunity stage unchanged for a defined number of days\ No customer engagement activity within a specified timeframe\ Deals approaching close date without recent interaction\ Accounts with declining meeting participation These definitions determine the operational conditions monitored by the platform. ### Signal Thresholds Thresholds determine when a signal should be triggered based on operational activity. Examples include: Days of inactivity before engagement decline is detected\ Number of days an opportunity remains in a stage before being considered stalled\ Minimum engagement levels expected for late-stage opportunities These thresholds allow organizations to align signal detection with their sales cycle and pipeline velocity. ### Signal Categories Signals are grouped into operational categories representing different aspects of revenue performance. Examples include: Pipeline progression signals\ Customer engagement signals\ Forecast risk signals\ Account expansion signals Categorization helps teams understand the operational context of detected signals. ### Signal Responses When signals are detected, the platform can initiate several responses. Examples include: Displaying signals within the conversational interface\ Sending alerts or notifications to revenue teams\ Triggering AI Revenue Agents to coordinate follow-up actions\ Including signals in executive reporting or pipeline reviews These responses ensure signals translate into operational awareness and action. *** ## How Signals Engine Setup Works The Signals Engine evaluates operational data retrieved from systems connected to the Alysio platform. These systems may include: CRM platforms such as Salesforce or HubSpot\ Customer engagement platforms\ Communication and meeting activity systems\ External intelligence providers The engine continuously analyzes activity across these systems and evaluates it against configured signal definitions. When conditions match the configured criteria, the Signals Engine generates a signal event that becomes available across the Alysio platform. Signals may then be surfaced through conversational queries, alerts, or AI Revenue Agent workflows. *** ## Example Configuration A revenue operations team configures the Signals Engine to detect stalled opportunities. The configuration may include: Condition: Opportunity stage unchanged\ Threshold: 14 days\ Scope: Opportunities in mid or late pipeline stages Once configured, the Signals Engine continuously evaluates pipeline activity. If an opportunity remains in the same stage for 14 days or longer, the platform generates a stalled opportunity signal. Revenue teams can then ask Alysio: “Which opportunities are currently stalled?” The platform retrieves signals generated by the Signals Engine and returns the relevant opportunities. *** ## Operational Impact Proper configuration of the Signals Engine improves how organizations monitor operational revenue activity. Organizations commonly experience benefits such as: Earlier detection of pipeline risk\ Improved visibility into engagement changes\ Faster response to stalled opportunities\ More consistent monitoring of pipeline health These improvements allow revenue teams to move from reactive reporting toward proactive operational awareness. *** ## Platform Data Flow The Signals Engine operates across several components of the Alysio platform. Connected Revenue Systems (CRM, Engagement Platforms, Communication Systems)\ ↓\ Operational Data Retrieval\ ↓\ Alysio Signals Engine\ ↓\ Signal Events Generated\ ↓\ AI Revenue Agents, Alerts, and Conversational Insights Diagram Alt Text Diagram illustrating how operational data from connected revenue systems flows into the Alysio Signals Engine, where patterns are analyzed and signal events are generated for alerts, agents, and conversational insights. *** ## Summary The Signals Engine is responsible for detecting meaningful operational patterns across the revenue stack and transforming those patterns into actionable signals. By configuring signal definitions, thresholds, and response behaviors, organizations can ensure that important operational conditions are detected early and surfaced across the Alysio platform.