Do you remember Einstein Copilot, being released at the beginning of 2024? Recently, Salesforce changed and enhanced it to Agentforce. At the base of Einstein Copilot was a mechanism called Chain-of-Thought Reasoning (CoT). CoT enabled Copilot to build a map leading to the goal, pretending how we - humans - make decisions. However, it came across as not being similar to human intelligence. While conducting scrupulous testing and developments, Salesforce came up with something much smarter and more handy - Agentforce.
So, what's behind Agentforce? What makes it better than Einstein Bots? What's its influence on business? Let's try to understand together.
What is Salesforce Agentforce?
Agentforce is Salesforce's innovative platform that aims to change human-AI cooperation. It's a kit of agents crafted for various tasks in sales, service, marketing, and other departments. Salesforce presents these intelligent agents to perform a variety of tasks, from providing 24/7 customer support to conducting internal operations. Also, Agentforce enables businesses to create custom, AI-driven virtual assistants. By leveraging familiar Salesforce tools like Flows and Apex, even team members without extensive coding experience can build intelligent agents.
Key features and benefits of Salesforce Agentforce include:
Automation: Automate routine tasks and processes to improve efficiency and reduce human error.
Integration: Integrate with your existing Salesforce ecosystem and other third-party applications.
Intelligence: Agents can learn, adapt, and provide relevant information.
Customization: Tailor agents to your specific business needs using pre-built templates.
One of the best benefits of Salesforce is its customization capability. For instance, while an ordinary bot conducts the conversation with a customer, they most likely need a human to jump in. But thanks to large action models (LAMs), Agentforce's bots are able to take action. This means that if a customer wants to book a hotel room, the bot will provide them with options and conduct the booking based on the customer's requirements. While doing business this way, and customizing your agents to your needs, your services can always be available. Which business wins: the one with service available around the clock or the competitor with eight working hours per day?
How Does Salesforce's Agentforce Work?
Agentforce, previously Copilot, is the peak of Salesforce's AI evolution. By leveraging advanced language models (LLMs) and large action models (LAMs), Agentforce empowers you to create intelligent, autonomous agents. Unlike Copilot, which was primarily designed to assist humans, Agentforce agents can operate both autonomously and collaboratively. They can handle customer interactions directly, without human intervention, or work alongside human agents.
With the user-friendly interface of Agent Builder and Agentforce Studio, even non-tech users can customize agents using natural language descriptions. The LLM interprets these prompts and maps them to specific actions while the LAM processes available data to determine the optimal course of action. Whether you need a sales coach, a customer service representative, or an SDR, Agentforce can create a tailored agent to meet your current needs.
Now, to get better acquainted with Agentforce's capabilities, let's take a look at two pillars it stands at:
Data Cloud
Data Cloud serves as a unified data foundation, seamlessly integrating data from various sources, including Salesforce clouds and external systems. So, if an agent requires information that isn't stored in Salesforce, users can set up regular data transfer from that extra source to Data Cloud, making the context wider for the AI agent.
Atlas Reasoning Engine
Salesforce calls Atlas Reasoning Engine the brain of Agentforce. Remember the Chain-of-Thought Reasoning (CoT) of Einstein Copilot? Salesforce has replaced it with Reasoning and Acting (ReAct).
"In the ReAct mechanism, the system goes through a loop of reason, act, and observe until a user goal is fulfilled. This kind of looping approach lets the system consider any new information and ask clarifying questions or confirmations so that the user's goal is fulfilled as precisely as possible." - Salesforce.
With Atlas Reasoning Engine, AI takes the following way to problem solving:
Acknowledge the query.
Search for relevant information with retrieval-augmented generation (RAG).
Evaluate potential responses to provide the best possible solution.
A few words about RAG. It's a technique that allows for the automatic addition of relevant proprietary data directly into the LLM prompt. The prompts are augmented with relevant information from Data Cloud, enabling AI to generate more precise and contextually appropriate responses.
xGen-Sales and xLAM: What's behind Agentforce?
The key distinguishing feature of Agentforce agents is the newest AI models that stand behind them. Recently, Salesforce introduced xGen-Sales and xLAM, which are meant to empower AI agents. Why are them game-changers?
Let's figure out.
xLAM
xLAM stands for a family of Large Action Models. Unlike LLMs (Large Language Models), LAMs are meant to generate actionable inputs, not only text answers. xLAM family, developed by Salesforce, includes models, each optimized for specific tasks. For instance, the xLAM-1B-fc-r model, called "Tiny Giant," is here to upgrade on-device applications due to the model's compactness and efficiency. It's perfect for real-time tasks execution while computational power is limited.
xGen-Sales
Built especially for sales task, xGen-Sale allows Agentforce agents to coach sales reps, nurture pipelines, and provide real-time actionable inputs. All of these - without requiring oversight. Being LAM, xGen-Sale is tuned to execute tasks on its own, not only provide text recommendations for people.
Agentforce & Einstein Bot: What's the Difference?
If you just started shallowly browsing through the articles, hoping to find quick info about Agenforce, you might struggle to catch the difference between Agentforce & Einstein Bot. Both of these features offer smart assistance, generative AI, NLP capabilities, and more. So, let's compare these two to get to the bottom.
Capability | Agentforce | Einstein Bot |
Customization | Simply to customize through Agent Builder using natural language description | Limited customization through bot builder |
Data Processing | Analyze data from various sources in real-time | Analyze data from set in advance sources |
Autonomy | Is able to make action by it’s own, due to xGen-Sales and xLAM models | Bases on flows set beforehand. Needs human intervention |
Task-performing | Is flexible to various tasks and domains | Is good at familiar tasks and domains |
AI Learning | Acquire knowledge from interaction experience | Needs manual updates |
While traditional chatbots often require human oversightі, Agentforce agents are designed to operate mostly independently. They can analyze data, make decisions, and take actions without human intervention.
Agentforce Use Cases
Agentforce for Service
Your new smart service agent keeps dealing with customers' issues 24/7. Unlike stundart agents, this one can conduct human-like conversations with those who need assistance. Being connected to the entire business, as well as knowledge base articles, agents can help to exchange purchases, change booking dates, and more, depending on your business. Although the agent is not human, it can even analyze sent images and handle much more complex issues than typical bots.
Agentforce for Sales
Smart agents in Salesforce can now help you with qualifying inbound leads. Each of the sales reps can have their own assistant for this task. While configuring the agent, the user can choose its language of communication, tone of voice, topics to discuss, and other rules of engagement. Also, the user can choose which group of leads the agent should contact. To conduct a higher quality communication, agent could be equipped with the pieces of content from the knowledge base.
Agentforce for Marketing
The marketing campaign agent helps conduct campaigns based on predefined goals and KPIs. The agent here is like one more marketing specialist in your team who can collaborate with you in a dialogue, answering the natural language descriptions. After fulfilling the guide table, you can "discuss" extra details. The agent can segment your audience, craft email drafts, and even create a customer journey map. The map variations can be adopted and changed depending on prospects' various interactions with your website.
Salesforce Agentforce: Conclusion
In conclusion, Salesforce's Agentforce, powered by xGen-Sales and xLAM, represents a significant leap forward in AI-driven automation. By seamlessly integrating advanced language and action models, Agentforce empowers businesses to build intelligent agents capable of not only understanding and responding to queries but also proactively initiating actions. This shift from passive assistance to active problem-solving has the potential to shift customer service, sales, and numerous other business processes. Agentforce Studio offers a user-friendly interface, making it accessible to a wide range of users. With its ability to automate workflows, Agentforce is poised to become a tool from the newest AI generation for businesses seeking to cut team workload.
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