Agentforce builder is the platform where we can build agents to engage with clients using using natural, conversational language that is routed through a large language model (LLM) and a reasoning engine to help it understand and retain context and make decisions based on the instructions and guardrails you set up. It helps you build and deploy AI agents using your existing workflows, data, and integrations. In this blog, let us explore Agentforce agents in Salesforce.
Agentforce agents are built to make intelligent decisions, can initiate and complete a sequence of tasks, handle natural language conversations, and securely provide relevant answers drawn from business data.
When building an agent using Agentforce, users with Agentforce Builder permissions can customize and configure the agent according to their needs. The types of Agentforce agents available within the Salesforce ecosystem depend on the Salesforce licenses assigned to the organization.
How an Agentforce agent differs from Einstein bot?
The below table describes the differences between a bot and an AI agent in detail.
| Bot | AI agent |
| Require a lot of expertise and time to set up | Requires less configuration |
| Based on pre defined rules, decision trees and scripted responses. | capable of reasoning, planning, and taking actions independently |
| Require substantial training and fine tuning for better accuracy | Training process is simpler |
| Often operates within a defined scope or knowledge base. | Can engage in more nuanced and context-aware interactions. |
| Structured data is needed | Can be grounded in both structured and unstructured data |
| Can understand natural language, answer questions, provide information and engage in dialogues within a limited scope of knowledge | Analyze complex situations, make independent decisions, interact with multiple tools, and execute multi-step tasks to achieve a defined objective with the help of LLM. |
| Ideal for customer service FAQs, lead qualification, simple transactions, and guiding users through structured processes, such as booking an appointment. | Ideal for tasks requiring proactive problem-solving, complex automation, multi-tool orchestration, or autonomous decision-making, such as dynamic order fulfilment. |
Einstein Bots require a lot of expertise and time to set up, and they’re based on complex, strictly defined conversational rules whereas Agentforce is flexible and requires less configuration because it’s powered by an LLM.
Below listed are some actions an AI agent can take care of
- Summarize Salesforce records
- Draft or revise emails.
- Find and update Salesforce records.
- Aggregate Salesforce data.
- Answer questions with information from your knowledge base.
How Agentforce integrates with Einstein Trust layer
Agentforce integrates with the Einstein Trust Layer, a secure AI architecture built into the Salesforce Platform. You get the benefits of generative AI without compromising customer data, and you can use trusted data to enhance AI responses. It works in the following ways.
- Data grounding: The Trust Layer grounds and enriches generative prompts with trusted company data.
- Zero-data retention: Your data stays safe; it’s never retained by third-party large language model (LLM) providers.
- AI monitoring: AI interactions are logged, giving you visibility into each user interaction
We will see the capabilities of agentforce agents in detail in the upcoming articles.
To learn more, click Agentforce 360 Platform (Formerly Salesforce Platform) | Salesforce
