DEV Community

Cover image for What are the technologies used in Agentforce?
Zoya
Zoya

Posted on

What are the technologies used in Agentforce?

Agentforce Service Agent utilizes a seamless integration of advanced technologies to offer its innovative solutions. This includes a dynamic combination of tools, from the powerful Atlas Reasoning Engine to the versatile Prompt Builder, ensuring enhanced performance and efficiency.

Let’s deep dive into all of the component technologies that form the basis of Agentforce:

1. Agent Builder
The Agent Builder allows businesses to rapidly design and customize AI agents for any specific role, use case, or industry. With this tool, organizations can create task-specific agents by defining a topic, providing NLP-based instructions, and setting up a library of actions for agents to follow. This allows for highly adaptable agents tailored to your business needs.

In addition, users can easily monitor the agents' planned actions and test their responses within the Agent Builder interface.

2. Atlas Reasoning Engine
As the core intelligence behind Salesforce Agentforce Agents, the Atlas Reasoning Engine enables agents to respond naturally and adapt quickly to evolving scenarios. This functionality makes agents more efficient, ready to multi-task, and increases their relevance within a team.

The engine enhances agents’ understanding and accuracy, categorizing customer requests based on predefined scopes and rules. This helps guide agents on appropriate actions they can take and what limitations they have. For each topic, detailed instructions and actions are provided, ensuring clarity on tasks such as order verification or gathering more customer details.

Atlas Reasoning Engine utilizes advanced techniques like Retrieval-Augmented Generation (RAG), combining various language models to boost the quality of responses. It retrieves relevant information and evaluates responses, while also granting agents access to searchable public data to better assist users.

3. Trust & Guardrails
Agentforce equips teams with the ability to set clear rules or guidelines for their AI agents, using natural language to define their roles and responsibilities. These guidelines ensure that agents handle the right queries and escalate more complex requests to human agents when needed. This smooth handoff process, along with a conversation summary, ensures a seamless experience for customers.

Moreover, Agentforce prioritizes security through the Einstein Trust Layer, which guarantees that Salesforce data remains protected and is never accessed or stored by third-party AI models. This strong layer of security allows organizations to safely deploy AI agents capable of managing multiple tasks while knowing when to escalate more intricate issues to human experts.

4. Model Builder
The Model Builder is a user-friendly, low-code platform that allows businesses to easily integrate custom AI models and large language models (LLMs) into their Salesforce environment. Users can retrieve API keys for their preferred LLMs, run tests in a sandbox environment, and activate these models within their Salesforce Org. With the help of Prompt Builder, organizations can seamlessly customize their AI tools for specific business needs.

5. Prompt Builder
Prompt Builder is the first step in creating personalized generative experiences. It allows users to easily customize pre-built prompt templates using their CRM data or information from Salesforce Data Cloud. This ensures higher-quality outputs tailored to the business's unique requirements.

By integrating Prompt Builder into daily operations—whether as part of an automated workflow, a Lightning record page, or agent actions—users can enhance their processes and achieve more accurate, contextually relevant results

Top comments (0)