AI technology is evolving in waves, with each new advancement in industrial, predictive, and generative AI offering previously impossible capabilities and opportunities. Today, autonomous agents represent another big leap forward in the evolution of AI.
Autonomous agents are advanced AI apps that are capable of understanding and responding to human inquiries without human intervention. Unlike AI systems that must stick to predefined rules, autonomous agents can carry out more complex tasks, interact with users conversationally, and continuously learn new skills.
Because these autonomous agents can handle more complexity, you might think that building one would be equally complicated. But that’s not necessarily the case. To understand this further, we’ll look at some of the tasks that autonomous agents can perform for human counterparts, the different kinds of agents, and how to build one with Agentforce on the Salesforce Platform using MuleSoft’s AI Chain technology.
What kinds of tasks can autonomous agents perform?
Just as every employee brings their unique skills to the table, autonomous agents are trained to be proficient at certain tasks. This allows employees to focus on more strategic and creative aspects of their work, alleviating the burden of repetitive and time-consuming tasks, which leads to increased job satisfaction and productivity. For customers, the benefit is faster, more accurate, and consistent service, enhancing their overall experience and satisfaction with the company.
Agentforce is a suite of tools for creating and customizing agents – both assistive and autonomous. For example, you could use Agentforce to build an autonomous agent capable of retrieving data from disparate systems in your organization and acting on your behalf. These actions could include:
- Checking inventory in your ERP systems
- Retrieving account details from your CRM
- Retrieving information about sales leads from your sales software
- Ordering new tech hardware from your asset ordering portal
- Showing employee information contained in your human capital management platform
You can also build autonomous agents that read and analyze image content or extract fields and data from PDF files. No matter the use case, a key factor in an autonomous agent’s usefulness is its ability to act in many different systems and applications. When it comes to enabling true autonomy, connectivity is key.
This is where MuleSoft integration technology shines in AI app development within the Salesforce Platform. MuleSoft bridges Salesforce’s capabilities with your wider enterprise ecosystem, allowing apps like autonomous agents built with Agentforce to work freely without hitting dead ends or roadblocks as they carry out their tasks.
What are the different types of agents?
What sets an Agentforce agent apart is its ability to independently handle tasks from start to finish. It can search for relevant data needed for a specific request, analyze that data to develop an effective action plan, and then execute the plan to complete the task efficiently and accurately.
Here are just a few examples of autonomous agents that can be built with low-code tools from Agentforce:
- Agentforce SDR: Engages with prospects 24/7, answering product questions, handling objections, and booking meetings for sales reps. This agent ensures responses are accurate and based on your business data, allowing sales reps to focus on building deeper customer relationships.
- Agentforce Service Agent: Provide 24/7 customer support, including service requests, resolving cases, and answering inquiries with generative AI. It operates across multiple channels, such as self-service portals and messaging apps, to deliver efficient and accurate customer service.
- Agentforce personal shopper: Give customers a digital concierge on e-commerce sites or messaging apps like WhatsApp. Offer personalized product recommendations and assist with customer search queries while learning from their behaviors to continually enhance their shopping experience.
The examples provided are just a small snapshot of what Agentforce agents can do across functions including finance, analytics, and HR. With this flexibility, Agentforce agents are capable of handling tasks across various departments, offering customized solutions that meet specific operational needs and boost efficiency. However, to fully harness the potential of these agents, you need advanced technology like MuleSoft’s AI Chain to ensure seamless integration across your systems.
Building an autonomous agent with MuleSoft AI Chain technology
MuleSoft’s AI Chain is a cutting-edge project that enhances the MuleSoft ecosystem with advanced AI capabilities, providing low-code and no-code tools that make it easier for developers to build smart applications. With dynamic tooling through a simple configuration file for flexible and customizable AI integrations, complete lifecycle management of AI agents via the MuleSoft Anypoint Platform.
Here’s a detailed look at each stage in the lifecycle of building an autonomous agent and the corresponding MuleSoft tools.
1. Design agent specs
This stage involves defining the specifications and requirements for the autonomous agent, including its capabilities, data inputs, and expected outputs. Anypoint Design Center allows you to design APIs and integrations with a user-friendly interface, ensuring that all specifications are clearly defined and documented.
2. Prototype and mock
Creating prototypes and mockups helps visualize the agent’s functionality and behavior before actual development begins. This stage is crucial for validating ideas and making necessary adjustments early on. Anypoint Design Center lets you create API specifications and mock services to simulate and test the agent’s interactions.
3. Share prototypes
Sharing prototypes with stakeholders for feedback ensures that the design meets business requirements and user expectations. This collaborative step helps in refining the agent’s design. Using Anypoint Exchange, you can share APIs, templates, and other assets with your team and stakeholders, facilitating collaboration and feedback.
4. Build workflows
Developing the actual workflows and logic that the autonomous agent will follow. This stage involves coding and integrating various components to create a functional agent. Anypoint Studio is a powerful IDE for designing, building, and testing APIs and integrations, providing a drag-and-drop interface for creating complex workflows.
5. Test agents
Testing is essential to ensure that the agent functions correctly and meets all specified requirements. This stage involves unit testing, integration testing, and performance testing. Anypoint Studio MUnit is a testing framework integrated with Anypoint Studio for creating and running automated tests for your APIs and integrations.
6. Deploy
Deploying the agent to a production environment where end-users can access and use it. This stage involves configuring the deployment environment and ensuring the agent is ready. Anypoint Runtime Manager provides a centralized platform for deploying, managing, and monitoring your applications and APIs.
7. Secure interactions
This stage involves ensuring that all interactions with the agent are secure and compliant with relevant security standards. This stage involves implementing authentication, authorization, and other security measures. Anypoint API Manager and Flex Gateway help you manage and secure your APIs, providing features like policy enforcement, threat protection, and access control.
8. Operate agents
Manage the day-to-day operations of the agent, including monitoring its performance, handling errors, and making necessary adjustments to ensure smooth functioning. With Anypoint Visualizer, you can get a visual representation of your application network, helping you understand and manage the interactions between different components.
9. Monitor agents
Monitor the agent’s performance and health to detect and resolve issues promptly. This stage involves setting up alerts and dashboards to track key metrics. Anypoint Monitoring is a monitoring solution that provides real-time insights into the performance and health of your APIs and integrations.
10. Publish and reuse
Finally, the agent and its components should be published for other teams or projects to reuse. This promotes the reuse of assets, reducing development time and effort for future projects. Anypoint Experience Hub is a platform where you can publish and share your APIs, templates, and other assets, making them easily discoverable and reusable by others.
Enable autonomy through connectivity
Want to know more about building autonomous agents with MuleSoft’s AI Chain technology and the Salesforce Platform? Check out our YouTube channel or join our community on LinkedIn.
