AI Agents

AI agents are autonomous workers that handle outreach, follow-ups, meeting booking, and lead qualification on behalf of your sales team. Each agent operates independently, working leads 24/7 based on the persona and rules you define.

Key Concepts

Templates vs. Agents

ScendCore uses a template-based system:

• Templates are blueprints that define personality, goals, channels, and autonomy settings. Templates do not work leads directly.
• Agents are instances created from a template and assigned to a specific team member. Each agent works that rep’s leads independently.

This means you define your playbook once in a template, then create individual agents for each rep who inherits those settings.

Agent Types

Channels

Agents can operate across multiple channels:

• Voice — Handles phone calls (inbound and outbound)
• Conversation — Email, SMS, WhatsApp, and chat
• Both — Voice + Conversation

Creating an Agent

Creating a Template

1. Go to AI Employees in the left sidebar
2. Click + New Template
3. Configure the template (see Configuration below)
4. Save your changes

Creating an Agent from a Template

1. On the AI Employees page, find your template under Master Templates
2. Click + Create Agent
3. Select the team member this agent will belong to
4. Click Create Agent

The new agent inherits all settings from the template and is assigned to the selected rep.

Configuration

Each agent (or template) has several configuration tabs:

Overview

Basic information about the agent:

• Name — The agent’s display name
• Type — SDR, Receptionist, Recovery, etc.
• Channel — Voice, Conversation, or Both
• Objective — What this agent is trying to achieve

Configuration

Core personality and behavior settings:

• Business description — What your company does (gives the AI context)
• Custom instructions — Specific rules or guidelines for the AI to follow
• Greeting — The opening message or script for voice calls
• Qualification framework — How the AI qualifies leads (e.g., BANT)
• Booking URL — Calendar link for meeting booking (Calendly, Cal.com, etc.)
• Escalation triggers — Keywords or situations that trigger escalation to a human
• Voice — The TTS voice used for phone calls (Neural2 voices)

Knowledge Base

Upload documents that the agent can reference during conversations — product sheets, FAQs, pricing guides, etc.

Channels

Assign phone numbers, SMS accounts, WhatsApp accounts, and email sender profiles to the agent.

Skills

Enable or disable specific capabilities:

• Schedule management (book meetings, check availability)
• CRM writes (create/update contacts, log activities)
• Sequence enrollment
• Document generation (PDF, DOCX, PPTX)
• Web search and competitive intelligence
• LinkedIn lookup
• SMS sending

MCP Connections

Connect external tools via the Model Context Protocol (MCP), such as HubSpot CRM integration.

Autonomy Levels

Autonomy controls how much independence your AI agent has. There are four levels:

How Risk Scoring Works

Every job the AI creates gets a risk score from 0 to 1. The risk score is compared against the agent’s risk threshold to determine if approval is needed:

• Risk below threshold — Job auto-sends (at Controlled or Full autonomy)
• Risk at or above threshold — Job goes to the approval queue

The risk threshold is dynamic and adjusts based on the agent’s confidence score, which is calculated from:

Increasing Autonomy

To increase an agent’s autonomy level:

• The confidence score must be at least 50/100
• The agent must not be in email warmup mode
• The agent cannot exceed level 3 (Full Autonomy)

Tip: Start new agents at the “Supervised” level. As the AI learns from your approvals and edits, its confidence score increases, and you can gradually raise the autonomy level.

The Kill Switch

Owners can activate the Kill Switch from the AI Employees page. When active, it immediately halts all AI agent activity across the workspace — no messages are sent, no calls are made. This is a safety mechanism for emergencies.

Click the Kill Switch button again to resume normal operations.

Job Lifecycle

Every action an agent takes follows a strict lifecycle:

Pending --> Approval Required --> Queued --> Executing --> Completed
                |                    |           |
                v                    v           v
            Cancelled            Cancelled    Failed / Cancelled

1. Pending — Job is created and risk-scored
2. Approval Required — Risk exceeds threshold; waiting for human review
3. Queued — Approved (or auto-approved); waiting for the worker to pick it up
4. Executing — Worker is actively sending the email/SMS/call
5. Completed — Successfully delivered
6. Failed — A system or provider error occurred
7. Cancelled — Rejected by a human, or halted by the kill switch

No job can skip states or go backwards. This ensures a complete audit trail for every AI action.