Salesforce Agentforce Real-Time Project Implementation

Building Real Time AI Agents Using Agentforce, Data cloud, RAG, Prompt Builder, Apex, Flows, Integrations, Slack

Welcome to the Salesforce Agentforce Real-Time Project Implementation Course, where you'll learn to build AI agents in real-world scenarios.

The demand for Agentforce is growing rapidly, yet many Salesforce professionals still lack hands-on experience. This course is designed to bridge that gap by guiding you through practical projects that help you build real-time AI agents with confidence.

Whether you're learning Agentforce for the first time or building a POC for your clients, this course offers hands-on experience and the confidence you need to work effectively with Agentforce. you will build Projects that you can confidently explain in an Interview , You’re encouraged to share them with recruiters and hiring managers.

in this course, we’ll build real time projects from scratch:

1. Roomie Agent

In this project, we’ll begin by building our very first AI Agent — Roomie, a virtual assistant for a luxury hotel website. This is a beginner-friendly project that introduces you to the foundational concepts of Agentforce.

You’ll learn how to:

• Create your first Agentforce AI Agent

• Define reusable actions that power specific tasks like room service and food ordering

• Train the agent to ask the right questions at the right time

• Leverage context to offer personalized and accurate responses

• Integrate the agent with a customer-facing Experience Cloud site, accessible to any hotel guest — no login required

Roomie is designed to assist hotel guests throughout their stay. It can:

• Help onboard new customers

• Assist with food order placement

• Handle room service requests

• Support users during the checkout process

You’ll also get hands-on with:

• Defining Topics that translate into real agent capabilities

• Adding instructions and actions that guide the agent in performing tasks

• Building custom actions using Flows and Apex

• Creating dependent actions, where the output of one action feeds into the next

By the end of this section, you’ll have built a fully functional AI assistant that simulates a real-world hospitality use case — laying a strong foundation for more advanced projects ahead.

2. Clinical Research Agent (Frontend) And Post Enrollment Agent (Backend)

In this project, we’ll take a major leap and build a much more advanced AI agent — the Clinical Research Agent. This agent is designed for the healthcare and research industry, capable of answering detailed patient queries around clinical research, trial eligibility, and company-specific studies.

You’ll learn how to:

• Equip your Agent to Answer User's question by utilizing Agentforce Data library

• Build Complex Agent Actions using Knowladge Prompt templates, Apex , Flows and API's

• Solve business Use case with Less code and Less Record Creation by giving Agent Access to Unstructured Business Data and Train it to take intelligent Actions.

• Work With Context Variable to get all the Share all the details with Agent before the Conversation starts with Customer

• Work with Multiple Agents to divide the Task Among them, the Front end agent to talk with Customer and Backend agent to perform backend Analysis and Execution

This agent uses several features of Salesforce Einstein AI and Agentforce, including:

• Agentforce & AI Agents

• Data Cloud and RAG

• Agentforce Data Library

• Prompt Builder

• Context Variable

• Complex Actions using Apex ,flow , API

• Invoking Agent with Record Triggered flows

By the end of this section, you’ll be capable of building production-grade AI agents for critical, high-impact industries like healthcare and research

Note:

• Code and Prompt Templates Built in Lectures will be provided in the Respective lectures.