Agentforce comprises two main components, namely the predefined AI agents by Salesforce and the agent-building platform. Now, predefined AI agents are created by Salesforce to cater to the business’s common tasks, which are often found in any business. These agents help the employees to fast-track their work and can even directly help the customers, eliminating the need for an extra person. However, if your business procedure requires a custom approach, you can do that too by creating or customizing your agent. 

Now comes the safety and data security part of Agentforce, which employs the Salesforce Einstein Trust Layer for data protection. This trust layer in Agentforce allows you to get engaged in control over data usage and protection. But what makes Agentforce different from the already existing copilots for businesses? 

Well, the difference is its ability to think and use logic like a human. It uses the Atlas Reasoning Engine, a new engine for Agentforce to help it understand the employee’s or customer’s query like a human and respond accordingly. Since it has access to the rest of the Salesforce infrastructure and the data, it filters out the most relevant data to reason and answer a query. 

Creating and deploying an Agentforce Agent is a simple five-stepped procedure with which you can use the prebuilt agents by Salesforce or create one from scratch. Here’s how you can do it: 

To start with, you need to create an agent with a well-defined role. You can use the already existing agent, like the customer service agent. But you can also create a brand new agent or customize any of the existing ones as per your needs. In this step, you need to broadly define the role of the agent and the goals it has to achieve.

In order to work, the agent must have information, but this information should come from trusted sources, right? So, in this step, you need to provide the agent with the right sources of data. For instance, the customer’s information can be given to the Agentforce from your own CRM, which is by far the most trusted source for it. Moreover, to provide it with the knowledge required for its role, you can use information created by you or available in the public domain. 

Now that you have defined a role for the agent, it’s time to clearly define the actions of the agent. These actions are based on triggers, so when there is a predefined trigger that hits the agent, it will do the predefined action, like running a flow. 

To make sure that the agent has clear boundaries while responding or doing what it was created for, the Guardrails come into play. These Guardrails allow you to define the dos and don’ts for the agent to follow. Moreover, doing this is very simple, as these instructions can be added in the form of simple text. In addition to these natural language texts, you can also use the Einstein Trust Layer to enhance data safety. 

Lastly, choose the right channels for the agent. These channels are where the agent has to work, like WhatsApp, CRM, Slack, your website, etc. This will help to create an agent that helps you deliver as expected outcomes.

Here are the prebuilt AI agents from Salesforce that you can use in your business to leverage your business:

With this, Agentforce can interact with your customer, acting like a real human customer service agent. It can take the user query, apply human-like logic to understand it, and reply with the relevant solution in natural language. Since the answers come from your defined database, the trusted knowledge eliminates the chances of foul replies. 

As its name suggests, this agent skill is also a customer-facing skill, but it’s used to handle sales queries. It takes the sales and product-related queries to give the relevant solution again in any natural language. It is preferably used on channels like WhatsApp and SMS, where the most sales-related queries are expected. 

If you want to empower your sales agents with realistic sales pitches, then a sales coach is what you need. With a Sales Coach, you can practice pitches with an agent who acts like a real customer. Since it has access to your company’s data, it creates objections that are most likely to come up when you deal with real customers.

Moreover, you can even take it with you on a real call with the customer to get real-time help from this coach for the particular pitch you are doing. Another customer-facing agent is a personal shopper to help eCommerce businesses. This agent helps the customers choose your products wisely and provides a personalized guide to the customers.

Marketing is one of the most important parts of any business, so it should not be left behind in Agentforce. With the campaign agent, you can create a marketing campaign from end to another. It can create campaigns based on factors like customer journeys, audience segments, and briefs given by you. 

Let’s now look at the key features of Agentforce to help you understand better.

Some key features of Agentforce make it really different from others. While you have already read them above, here’s a brief about how they make Agentforce different from any other tool:

The agent builder in Agentforce allows you to create an agent without having hardcore knowledge of coding. It is a low-code platform where an agent can be created in minutes. You can customise it as you want using the existing tools, including Flows, Apex, etc.

For instance, a customer service manager wants to automate order status inquiries. Using Agent Builder, they select the “Order Management” topic, configure actions like “Retrieve Order Status,” and set escalation rules for complex cases. Without writing code, the manager launches an agent that can answer order queries and escalate to a human if the request is outside its scope

This reasoning engine for Agentforce is its brain. It makes the agent able to understand natural language. Moreover, by classifying the topics, categories, and scope of the response, you can ensure the right responses or actions by the agent.

Example: A user asks, “Can you create an order for the first product I mentioned?” The Atlas Reasoning Engine:

Guardrails and the Einstein trust layer in Agentforce allow you to restrict the agent from doing an unwanted action. It keeps the agent safe for both the user and the business. Moreover, the Einstein trust layer also ensures the agent can use any LLM safely without leaking data to the LLM model. 

For instance, a sales agent is restricted from accessing customer financial data unless explicitly authorized. If a user tries to prompt the agent for confidential information, the guardrails block the action and provide a safe response. The Einstein Trust Layer ensures that only approved data is shared with AI models, protecting both user privacy and business interests.

As you create an agent, it’s crucial to test it before launch. That’s where this testing feature comes in. It gives you an environment to test your agents with the help of synthetic test cases, which can even run in parallel. It will help your team to change the instructions of the agent to let it work the way it should. 

While Agentforce by Salesforce is undoubtedly a step forward in using AI for your business, it can be quite difficult for you to manage its execution on your own. That’s where we come on to help. At Streams Solutions, we offer businesses to execute Salesforce and its different suites to automate the business to the highest possibilities. With us, you can use Agentforce in your business and take it to new heights of automation. We will not only execute the Agentforce for you but also help you create your agents for your specific needs and integrate the other parts of Salesforce CRM into it. So, to get a 100% working execution of Agentforce in your business, reach us today!