Artificial intelligence (AI) is radically transforming the way companies interact with their clients, staying at the forefront is crucial. Companies are developing AI agents to automate tasks, improve efficiency and offer personalized experiences to their customers. However, the implementation and management of these intelligent agents can be a challenge. How to make sure they are working properly? How to optimize your performance to obtain the best results? And how to climb its use as demand grows?
What is Salesforce Agentforce 3 and why is it important?
Salesforce has just shown in a meeting with specialized media the new version of Agentforce 3, its application of proactive and autonomous that provides specialized and always active support for employees or customers. This new version of Agentforce offers great visibility and control over AI agents, allowing companies to expand their implementation effectively and maximize their impact.
In essence, Agentforce 3 acts as a control center for your intelligent agents, is the first complete solution of the life cycle of AI agents. It allows monitoring your real -time performance, identifying improvement areas and adjusting your configuration to optimize the results.
With the appearance of a new hybrid workforce, in which human beings and AI agents work side by side, customers demand tools that allow them to continue growing. They need a new way to develop faster, connect agents with reliable workflows, supervise the activity and continually optimize the performance of all equipment.
A unified experience
Agentforce Studio becomes the first unified experience to design, test, implement and optimize large -scale AI agents. This version also introduces safe support for open interoperability standards such as the models context protocol (MCP), the agentxChange platform expanded with more than 20 pre-validity MCP servers and a faster amortization time thanks to new predefined industrial actions with flexible prices and global availability. All driven by an improved Atlas architecture for higher speed, trust and scalability.
Greater visibility, monitoring of real -time AI agents
Visibility is key to ensuring that AI agents are meeting business objectives. Without adequate monitoring, it is difficult to know if they are working properly or if they need adjustments. Second, control allows optimizing their performance and adapting them to the changing needs of your business. You can adjust your configuration, change your rules and customize your behavior to improve the efficiency and customer experience.
In addition, agentforce 3 allows you to climb the implementation of AI effectively. As the demand grows, new AI agents can be added and managed centrally through the platform. This allows the most of the potential of AI without losing control or compromising the quality of the service.
Visibility is essential for any successful agents management strategy. Without a clear understanding of how intelligent agents are working, it is impossible to optimize their performance and ensure that they are fulfilling your goals. Agentforce 3 addresses this challenge in front, offering unprecedented visibility about the performance of your real -time AI agents.
With agentforce 3, key metrics can be monitored such as:
- Resolution rate: How many customer consultations are solving agents successfully?
- Answer time: How long does it take to respond to customer consultations?
- Error rate: How often do mistakes make or need the intervention of a human agent?
- Customer satisfaction: How do customers describe their interactions with AI agents?
This information allows you to quickly identify improvement areas and take measures to optimize the performance of your AI agents. For example, if an AI agent has a high error rate, you have to check its configuration and adjust your rules to improve your precision. Or if it is detected that customers are not satisfied with their interactions, it is possible to train them with new data and improve their ability to answer their questions.
In addition, agentforce 3 allows you to segment AI agents and analyze their performance per group or task. This helps identify the best practices and replicate them throughout the organization. For example, if it is discovered that a group of AI agents is solving customer consultations more efficiently than others, their strategies can be analyzed and shared with the rest of the team.
Adjust and optimize AI strategies for optimal results
Visibility is important, but control is equally crucial. It is not enough to know how AI agents are working; It is also necessary to have the ability to adjust and optimize your strategies to obtain the best results. Agentforce 3 offers total control over your AI agents, allowing customizing their behavior, adjusting their configuration and adapting them to the changing needs of the business.
IA agents are no longer experimental, they are becoming generalized, although their scalability remains a challenge. According to Slack Workflow, the use of AI agents has grown 233% in the last half year. In addition, 96% of workers say that AI allows them to complete tasks that they could not do before. And the obstacle is that most agent platforms lack the tools, governance and observability to climb beyond concept tests. Agentforce 3 changes this situation by providing full -life cycle tools, a safe interoperability and business level controls that organizations need to convert the speed of agents into their competitive advantage.
With agentforce 3 it is possible to customize the behavior of AI agents, define their rules, adjust their parameters and customize their tone to adapt them to the brand and customer preferences; Adjust your configuration, modify your configuration to improve your precision, your efficiency and their ability to solve customer consultations; Adapt them to the changing needs of the business, adjust the configuration of your AI agents to ensure that they remain relevant and effective.
When launching a new product or service, with agentforce 3, IA agents can be trained with relevant information and adjust their configuration so that they can answer customer questions precisely and efficiently. Or if it is observed that customers are having difficulty understanding the responses of AI agents, their language can be simplified and their tone of voice can be more understandable.
Optimized agentforce architecture
All new agentforce 3 capabilities are based on the Improved Atlas Trust and Reasoning engine, which provides a base prepared for the company, with less latency, greater precision, global availability and additional control options through LLM housed in the Salesforce infrastructure. With this, Salesforce customers will obtain, among other things, better performance and faster streaming response, greater variety of LLM with Anthropic hosted, greater precision thanks to the web search and online appointments or a greater geographical presence with the incorporation of more languages.
Agentforce 3 also introduces a simplified and flexible Price structure with new agentforce sku for sales, services and industrial cloud with prices per user and unlimited use of actions for agents who deal with employees, in order to help equipment quickly get up and climb their business.
Great deployment speed
One of the biggest challenges in implementing AI agents is integration with existing systems. Many companies face the complexity of connecting their new AI agents with their CRM platforms, ticketing systems and other essential tools. Agentforce 3 simplifies this process by integrating perfectly with the existing Salesforce platform through multiple actions.
To completely understand the Agentforce 3 potential, it is useful to observe how other companies are using the platform to transform their operations. During the presentation to specialized media, representatives of Salesforce chatted with Mamatha Chamarthi, Senior Vice President and Chief Digital Officer of Goodyear, world leader manufacturer in tires, which has launched an ambitious project to deal directly with its end customers.
Traditionally, Goodyear has operated exclusively through its distributors network, but the need to connect directly with end customers were raised. That is what they have been able to carry out in a project in which, in just in a few months, they have launched an assistant who, thanks to the previous information about each client is able to offer the appropriate products for their vehicles at the time when required.
During the demonstration, we were able to verify how the assistant managed through agentforce accesses the history of vehicles and purchases of the customer, together with the information from the sensorization of the connected car. The customer makes the consultation and, in a totally conversational way, the assistant is suggested products adapted to their needs as well as a selection of workshops in which to install them. The system facilitates the management of the previous appointment in which it fits the most with your needs and leaves everything ready for the visit. As the CDO of Goodyear highlighted, “to be a leader in your industry, you have to be a leader in your technology.”
Agentforce Studio with agentforce optimizer will be available in August. Native Agentforce compatibility with MCP is in a pilot phase in July and A2A compatibility will be available in a pilot phase at the end of the year. The MCP servers of the Salesforce API platform are currently in a pilot phase and there are already more than 100 predefined industrial actions available.
In summary, Agentforce 3 simplifies the implementation of AI agents when they are perfectly integrated with your existing Salesforce platform and offer an intuitive and easy to use interface. This allows you to begin to take advantage of the benefits of AI quickly and easily, without having to worry about the complexity of integration.
