What is Salesforce Agentforce? Technology Behind and Pricing

The launch of Agentforce is nothing other than a major upliftment in Salesforce’s innovation series. With a game-changing combination of assistive AI and autonomous AI, Agentforce has already started meeting expectations on what’s possible with Salesforce. 

Agentforce brings a powerful mix of augmented generative AI and autonomous agents; where assistive AI helps with accomplishing tasks like summaries and sales emails and autonomous AI, enable agents to intelligently make decisions and act without a person controlling it full-time.

This new vision of AI is not here to replace humans, but to augment overall productivity and deliver customer success with humans and agents working together. 

In this blog, we’ll take a closer look at what Salesforce Agentforce really is. We’ll explore how it brings together people, AI, customer relationship management (CRM), and data to create a smoother experience for everyone involved. 

Let’s dive in!

What is Salesforce Agentforce?

Agentforce is a comprehensive AI platform integrated into the Salesforce ecosystem, designed to create and manage autonomous agents that can perform a wide range of tasks.

Agentforce AI agents are dynamic and adaptive. They can understand and reason through conversations, build plans to address issues and take the best course of action using available tools.

This application-based agent provides users with the required information to deliver their respective tasks. 

Key components to Build Agentforce Agent

Here’s a breakdown of key elements that Agentforce comprises, along with insights on how to approach each one strategically.

1. Role: Defining Purpose and Scope

The Role component is the foundation of your agent, it’s similar to a job description. It clearly outlines:

• Primary Responsibilities and Objectives: What tasks will the agent perform?
• Specific Use Cases: Which scenarios will it handle?
• Target Audience: Who will interact with the agent?
• Success Metrics and Expected Outcomes: How will you measure its effectiveness?

For instance, a customer service agent’s role might be defined as “Provide first-line support for product inquiries while maintaining high customer satisfaction scores.”

Before understanding the Agent Builder, it’s important to conduct thorough research with your target users. The insights gained from this research should guide your decisions, ensuring that the agent’s purpose aligns with user needs.

2. Data: The Knowledge Foundation

Data acts as the brain of your Agentforce agent. This component includes:

• Access to Relevant Salesforce Objects and Fields: Ensuring the agent has the necessary data at its disposal.
• Integration with External Data Sources: Allowing the agent to pull in information from various platforms.
• Historical Interaction Data: Leveraging past interactions to inform future responses.
• Context-Specific Information: Providing relevant details based on user queries.

The quality and scope of the data you provide directly influence your agent’s decision-making capabilities. Remember the principle of Least Access: ensure that sensitive information is handled appropriately to avoid potential security breaches.

3. Actions: Enabling Response and Execution

Actions are what empower your agent to engage actively with users. This component encompasses:

• Pre-Built and Custom Functions: Tailoring actions to meet specific needs.
• API Integrations: Connecting with other systems for seamless operation.
• Workflow Triggers: Initiating processes based on user interactions.
• Automation Capabilities: Streamlining repetitive tasks.

Actions transform your agent from a passive information processor into an active participant in business processes, allowing it to create records, update data, and respond to queries effectively.

Even if you’re utilizing low-code tools and pre-built components, it’s essential to implement a formal DevOps process, including rigorous testing protocols.

4. Guardrails: Ensuring Safe and Compliant Operation

Guardrails are vital for maintaining safety and compliance in your agent’s operations. These mechanisms include:

• Data Privacy Controls: Protecting user information.
• Security Parameters: Safeguarding against unauthorized access.
• Ethical Guidelines: Ensuring responsible use of AI.
• Compliance Requirements: Adhering to legal standards.
• Response Limitations: Setting boundaries on what the agent can do.

Reviewing your data feed is crucial. In case certain information gets exposed, it could lead to a security breach, making implementation of robust guardrails imperative.

5. Channels: Enabling Multi-Platform Engagement

Channels dictate where and how your agent interacts with users. This component includes:

• Communication Platforms: Such as Slack, Email, or SMS.
• User Interfaces: The design and usability of interaction points.
• Integration Points: Connecting with other tools users may employ.
• Response Formats: How information is delivered back to users.

Effective channel configuration ensures that your agent is accessible in the environments where users need it most. Remember that testing must encompass all selected channels, testing in one platform (like Slack) does not guarantee functionality in another (like Microsoft Teams).

Agentforce is designed to enhance every aspect of customer interaction, whether it’s in sales, service, marketing, or commerce. This isn’t just about automating tasks; it’s about creating meaningful conversations that lead to genuine connections and higher conversions.

What’s even more exciting is Salesforce’s vision of “Agentforce In Every App,” which means this technology can be integrated across various platforms, making it accessible to all facets of your business.

Technology Behind Agentforce: Customize Your Agent

Here is the list of the technology behind Agentforces’ foundations: 

1. Agent Builder

The low-key builder allows you to customize unique agents or even build your AI agents for any role, use case, or industry quickly. Organizations can create a job to be performed explicitly by agents by setting a topic, writing NLP-based instructions on that topic, and building a library of actions for agents to select from whenever needed. 

Users can easily track the plan of actions to be executed by an agent and test their responses in Agent Builder.   

2. Atlas Reasoning Engine

Known as the brain behind Agentforce Agents, it helps users to make agents revert naturally and adapt to scenarios as quickly as possible. This makes them ready to function faster, multi-task, and become more relevant to the team.

Atlas Reasoning Engine boosts agents’ accuracy and understanding of the assigned topics and classifies customers’ requests into a category with set scopes and rules, giving direction to agents on which actions they can take and which they can’t. 

To help users effectively, each topic comes with clear instructions and actions. These might include checking order details or gathering additional information. The reasoning engine is designed to enhance this process by using advanced methods like Retrieval Augmentation Generation (RAG). This technique employs various language models to improve the quality of queries, ensuring that the most relevant information is retrieved while also assessing how good the responses are. Additionally, agents now have access to searchable public data, which further supports their ability to assist users.

3. Trust & Guardrails

Agentforce allows teams to create a clear set of rules or guidelines for their AI agents through simple and natural language. This helps in defining the topics an agent should handle and sharing precise instructions on when to escalate a query to a human agent. By establishing these guardrails, teams ensure that the agents operate effectively in their respective assigned roles. 

Suppose a customer inquiry exceeds the AI agent’s capabilities. In that case, it can be easily handed off to a human representative, summarizing the conversation and providing essential details to make the conversation smooth.

Additionally, Agentforce prioritizes data security through the Einstein Trust Layer, which ensures that no Salesforce data is accessed or retained by third-party AI model providers, allowing organizations to use large language models (LLMs) safely. With these robust security measures in place, users can confidently deploy AI agents that can autonomously manage a variety of tasks simultaneously having the conscience to escalate more complex issues to human experts when necessary.

4. Model Builder 

Model Builder is a user-friendly, low-code tool that gives customers an easy way to register, test, and activate their custom AI models and large language models (LLMs) inside their Salesforce Org. Users can get the API keys for their preferred LLMs, experiment in their testing environment, and activate these models when it feels like using Prompt Builder, enabling businesses to customize their AI solutions and integrate them seamlessly into their Salesforce experience.

5. Prompt Builder

The prompt is the first step toward the creation of a generative experience. An excellent prompt builder makes it easy for users to personalize ready-to-use prompt templates with their own CRM or data available in Salesforce Data Cloud, improving the quality of results. 

The Prompt Builder integrates the generative experience into everyday tasks, whether it’s part of an automated workflow, a Lightning record page, or even in the actions performed by an agent. This way, users can enhance their work processes while receiving more relevant and tailored outputs.

Agentforce Is The Only One To Bring Human + AI + Data + Actions

Here is what happens when it takes charge of the following: 

Human + AI 

The most effective way to utilize AI agents is by having them work peacefully with humans and witness your customer experience reaching heights. These assistive agents handle time-consuming tasks, freeing up employees to focus on higher-value activities that contribute more to the revenue generation side. 

Additionally, autonomous agents also proactively manage specific tasks and escalate issues to human team members when necessary. For example, every new Account Executive (AE) can get trained by a personal sales coach who provides feedback, guidance, and support to help them excel in their roles.

Data

For AI agents to perform effectively, they need access to the correct data from trusted sources at the right time. With Salesforce Data Cloud, the team can create intelligent agents that have the necessary information for any employee or customer interaction. 

It enables users to leverage data from all parts of their organization, ensuring scalability and security while keeping up with enterprise-grade standards. This setup allows agents to be dynamic in the case of business processes and customers without putting data security in jeopardy.

Actions

An AI agent that cannot take meaningful action is just another bot. Agentforce agents are designed to perform actions across various systems, empowering teams to deliver tasks more efficiently. These agents establish a connection between data and action by revealing metadata about defined workflows and AI automation, which empowers them to undertake high-value tasks.

How does Salesforce Data Cloud Empower Agentforce?

Salesforce Data Cloud is at the heart of what makes Agentforce truly exceptional. It brings together all kinds of data, both structured and unstructured across different sources in real time.

This collaboration allows users to create a complete picture of customers and deliver personalized experiences that people didn’t see coming but will surely love, wherever they are (irrespective of communication channels and different touchpoints).

Here’s how Data Cloud is set to back Agentforce up:

Seamless Integration with Customer 360

With Data Cloud, Salesforce Customer 360 applications can tap into reliable customer data, which is essential for crafting personalized experiences and gaining real-time insights. Zero-copy technology and MuleSoft connectors are the technology behind Data Cloud, which is going to help pull data from different sources including data lakes and warehouses.

It can also transform various formats like PDFs, texts, and videos into useful information, creating detailed customer profiles stored as metadata. This metadata flows smoothly into Salesforce applications, giving every team a 360-degree view of the customer while keeping data secure.

With the belief in an open ecosystem that encourages customization, Salesforce has made it easy for users to create custom connectors and extend features. And the recent acquisition of Zoomin is the reason behind it. Here’s how: Zoomin helps Data Cloud to integrate unstructured content, allowing access to valuable enterprise knowledge from platforms like Google Drive and Microsoft SharePoint.

Contextual Data for Agentforce

Data Cloud uses advanced features like Retrieval Augmented Generation (RAG) and hybrid search to provide meaningful insights for Agentforce. RAG helps find the right data from various sources, while hybrid search combines semantic understanding with keyword searches to deliver precise information. The introduction of no-code retrievers makes it simple for users to set up customized data retrieval processes without needing technical expertise.

Thanks to its integration with the Atlas Reasoning Engine, Data Cloud allows agents to extract valuable insights from complex unstructured data. For example, Agentforce can connect product details found in customer images to relevant knowledge articles, helping support teams resolve issues more efficiently.

Autonomous Actions in Workflow

Data Cloud makes it easy for business users to access actionable data when they need it. This capability empowers sales teams to spot upsell opportunities and enables service teams to proactively meet customer needs. By making data accessible to everyone, Salesforce helps teams use insights to create more targeted interactions with customers.

Data Cloud takes things a step further by turning insights into immediate actions through integrated analytics and automation. With real-time capabilities, it supports Einstein Personalization and AI-driven recommendations that help teams make quicker decisions across various customer touchpoints. Automation through data-triggered workflows streamlines operations, while low-code tools ensure that everyone in the organization can easily access and act on data.

Agentforce leverages machine learning and generative AI insights from Data Cloud to deliver personalized recommendations. This means timely engagement with customers happens seamlessly across different channels like Slack and Tableau.

Agentforce Pricing and General Availability

Now, let’s discuss how much Agentforce costs.

Well, as an existing Salesforce customer using Foundations, you can get started with Agentforce free of cost for every Salesforce cloud you don’t have access to. This is available for the Enterprise edition and above. You also get 1k Agentforce conversations and leads, 250k Data Cloud credits, and Sales, Service, Commerce, and Marketing tools.

For the rest of the users, Salesforce Agentforce pricing is based on the number of conversations (frequency of interactions between customers and AI Agents). The cost per conversation is $2 with potential reductions for higher volumes of interactions.

The cost-effectiveness of Agentforce’s “conversations” will largely depend on the type and volume of interactions they replace, as well as whether these interactions yield success rates that are equal to or better than those achieved by human sales and service representatives. 

In addition to this, the following Agentforce AI agents are now generally available:

That’s not all that Agentforce has to offer. More operation-based and industry-based agents are expected to roll out soon.

A few components of Atlas Reasoning Engine will be available in February 2025.

The Final Take

To wrap it up, trusting and immersing your business processes and systems in this third wave of AI revolution can be both exciting and challenging. Being the no-code solution, Agentforce promises quick setups, but customizing agents to perfectly fit your business needs might call for extra: time, effort, and expertise.

You can find both effort and expertise at Cyntexa. As a part of the Agentforce Partner Network and a trusted Salesforce Summit Consulting Partner, we have a team comprising 400+ experts, including more than 170+ AI associates and 70+ AI specialists (and it’s just the beginning). We can help you securely build and deploy agents that are ready to hit the ground running.

Agentforce isn’t just another AI-based offering; it is expected to be a ground-breaking combination of AI with the personal touch that customers like. Whether you want to grow your service team or make your current work easier, Agentforce is the tool you need by your side. 

Curious about how Agentforce can make a difference for your company? 

Schedule a consultation with Cyntexa’s experts and get started on your AI journey!