Learn What Agentforce Is and How It Can Enhance Your Business

Solutions based on generative artificial intelligence (Gen IA) are accelerating process automation in all industries. Pragma recently attended Dreamforce, the event where Salesforce presented its most recent developments around this technology. Next, we want to talk to you specifically about Agentforce, one of the most interesting launches of the event, especially regarding its potential for the financial and retail sectors.

To understand the power of Agentforce and whether this solution adapts to your business’s needs, we will first briefly explain what an AI agent is for. From there, we will see how Agentforce simplifies the implementation of this solution and how technology works.

What Are Gen AI-based Agents?

In addition to using foundational models in AI, AI agents are systems that receive data from your company to build a knowledge base that allows them to perform specific tasks. For example, an AI agent can be trained with information from a bank or a retailer to support the work of the sales team with precise real-time information for the end user. 

Unlike traditional software or chatbots based on intentions, entities, and responses, AI agents can execute tasks autonomously. They often perform complex operations that previously required human intervention. To learn more about how AI agents are being implemented in all businesses, we invite you to read this article by Gregorio Patiño. 

What Is Agentforce? How Does It Simplify AI Agent Development?

Agentforce is the new Gen AI platform, an evolution of Einstein Copilot. It joins the Salesforce ecosystem to make a variety of AI agents available to all businesses. These agents are often already pre-designed with use cases in specific industries such as banking, retail, or health. Still, Agentforce also allows you to create fully customized AI agents efficiently and reduce development efforts. 

This is possible thanks to Agent Builder, a no-code tool that helps companies quickly design, personalize, and extend AI agents to adapt them to their specific use cases.

What makes Agentforce especially powerful is its integration with the broader Salesforce ecosystem, which includes Data Cloud, Slack, Tableau, and more. This integration ensures that AI agents can access and process Salesforce data and workflows and execute tasks accurately and efficiently. 

How Does Agentforce Work?

As we said before, the key to Agentforce’s power is its integration with the Salesforce ecosystem. Still, three key components make it stand out compared to other alternatives: 

• Atlas, the “brain” of Agentforce:
  

  Atlas is the engine that allows Agentforce to perform complex tasks. Unlike traditional systems that follow static and preprogrammed workflows, Atlas can adapt and improve its approach depending on specific tasks. It works as an engine of reasoning and planning for Salesforce’s AI agents. 

  For example, in the case of a customer service agent, Atlas makes a plan aligned with the specific objectives of that interaction. This process also implies the continuous assessment of:

  • Structured data: bank transaction data, inventory data
  • Demographic data: age, sex, location
  • Unstructured data: emails, posts on social media 

   

  Atlas also performs what is known as self-reflection, meaning it can adjust its actions dynamically as new information becomes available, ensuring that the agent’s responses are accurate and aligned with company goals.

• Advanced recovery mechanisms:

  Another characteristic of Atlas is the Retrieval-Augmented Generation (RAG). It is an AI technique that combines information recovery and text generation. 
  
  Given a query, Atlas seeks relevant information in its knowledge base and produces more precise and contextualized responses based not only on the information it has been trained on but also on data retrieved from different sources. 

• Technological tools, ethical and regulatory framework for the responsible development of AI solutions

  Another key component of Atlas is what it does not do. Through a guardrail system, we can determine the limits within which our AI agents will operate. This facilitates fulfilling security policies and protocols and prevents responses with incorrect or fictional content (hallucination) or harmful or inappropriate content (toxicity) while protecting from cyber-attacks aimed at live AI models.

Cases of Agentforce Use in the Retail and Banking Sectors

At Dreamforce, we can appreciate the power of AI in action. An AI agent trained to simulate customer service interactions demonstrated its ability to understand complex queries, access relevant information, and perform automated tasks like checking product availability. This technology has profound implications and can automate various processes in various industries. To illustrate this point, we will focus on two key sectors.

Retail Trade: Personalized Assistance and Campaigns

In the world of retail, user experience is everything. Agentforce AI agents can act as shopping assistants, providing personalized product recommendations based on customer preferences, browsing history, and purchasing patterns. For example, an agent can suggest products, guide customers through a website, and even help them purchase on a messaging app like WhatsApp.

Retailers can also use Agentforce for merchandising assistance. AI agents can create marketing campaigns, optimize product listings, and provide data-based information to improve the shopping experience. This automation allows retail teams to focus on higher-value tasks, such as strategy and customer acquisition, while AI agents handle routine tasks.

Banking: Financial Advisors and Fraud Detection

In the financial sector, Agentforce has two pre-designed agents. The banking agent interacts with customers autonomously, providing personalized assistance based on individual customer profiles. As in the previous example, this interaction can occur through different channels, such as WhatsApp or telephone calls. 

On the other hand, the financial agent can take on the functions of a digital financial advisor. This way, users receive personalized advice that helps them manage their savings, investments, and expenses. By leveraging CRM data and external financial information, these agents can proactively suggest ways for users to achieve their financial goals.

Another key application is fraud detection. AI agents can supervise financial transactions, analyze patterns, detect suspicious activities, and perform real-time actions.

Is Agentforce the Solution for Your Business?

Although Agentforce offers enormous potential, not all companies are ready to take advantage of it immediately. Salesforce AI agents require a significant level of data governance and organization. 

At Pragma, we recognize that some companies may need a gradual approach to adopting this type of technology, especially when integrating solutions based on Gen AI into their workflows.

The good news is that Salesforce offers flexibility and incredible ease of integration, which allows for company analytics.