Agents

Introduction to AI agents and building your AI Workforce!

What are Agents?

Agents are powered by LLMs that plan and complete tasks on autopilot. They are given tools, and decide how to use tools to achieve goals prompted by you.

Unlike traditional automation that follows rigid, pre-programmed rules, AI agents can:

• Think and reason through complex problems
• Adapt their approach based on context and feedback
• Learn from experience by storing successful patterns
• Make decisions about which tools to use and when
• Communicate naturally with humans and other agents

What are the benefits of an AI Agent?

Scales to meet demand

Agents can flex with your needs, handling seasonal or regional spikes in activity—especially useful in industries like education, hospitality, and finance.

Increases engagement

Automate repetitive tasks so your team can focus on high-value work. Sales teams, for example, use agents to qualify leads, freeing reps to close deals.

Learns from experience

If an agent doesn’t know something, it can escalate to a human, store the answer, and use it next time. Ours posts unknowns to Slack for fast input and learning.

Works solo or with you

Agents can run fully autonomously or in co-pilot mode. One of ours builds Webflow pages daily—no human touch required.

Responds flexibly

Unlike rule-based tools, agents adapt their responses to each task. A support agent might troubleshoot one day and resolve billing the next.

Available 24/7

Agents work around the clock without breaks, ensuring consistent service and response times regardless of time zones or business hours.

How AI Agents Work

Agents in Relevance AI can operate in different ways:

• Autopilot - They complete tasks independently.
• Human in the loop - Asking humans for input or approval when needed.

You can trigger agents to start work with:

• Pre-built integrations - Seamlessly connect with existing tools.
• API access - Use them in your applications.
• User interface - Run agents directly from our platform.

Where are Agents most useful?

AI agents excel in roles requiring consistent execution of complex but well-defined processes, such as:

• Customer Support: Handling routine inquiries, troubleshooting common issues, and escalating complex problems to human agents
• Sales Qualification: Engaging with prospects, gathering initial information, and identifying promising leads
• Content Creation: Generating drafts of routine documents, reports, and communications
• Data Analysis: Processing and summarizing large volumes of information to extract actionable insights
• Scheduling and Coordination: Managing calendars, setting up meetings, and sending reminders

Organizing your Agents

As you build and use more Agents, keeping them organized becomes essential for efficient workflows. Relevance AI provides several ways to manage and access your Agents:

Pinning Agents for quick access

Pin your most frequently used Agents to keep them easily accessible in the Relevance AI platform. Pinned Agents appear:

• At the top of your agents list in the main app
• First in the “Browse agents” section when creating a new chat

This makes it easy to quickly access the Agents you rely on most, without scrolling through your entire collection.

To pin an Agent, click the pin icon next to the Agent’s name in your agents list. You can pin multiple Agents and unpin them at any time by clicking the pin icon again.

Organizing with folders

You can organize your Agents into folders within your project, making it easier to categorize and find Agents based on their purpose, department, or use case. This is particularly useful for teams managing large numbers of Agents across different functions.

How to get the most from your Agents?

When inventing or creating an agent, you’d want to utilize domain expertise or model an agent after a Domain expert:

1. Start with clear objectives: Define specific tasks and goals for your agents
2. Provide quality knowledge bases: Equip agents with comprehensive, up-to-date information
3. Establish escalation protocols: Create clear paths for agents to involve humans when needed
4. Monitor and refine: Regularly review agent performance and make adjustments
5. Integrate with existing systems: Connect agents to your current tools and workflows
6. Organize for efficiency: Use pinning and folders to keep your most important Agents easily accessible

By thoughtfully implementing AI agents, organizations can enhance productivity, improve customer experiences, and free human employees to focus on work that requires creativity, empathy, and strategic thinking.

Frequently asked questions (FAQs)

Do I need coding knowledge to Invent an Agent?

No, Invent is specifically designed to make agent creation accessible to users without technical expertise. You only need to describe what you want your agent to do in plain English.

What are tools in the context of AI agents?

Tools are capabilities that agents can use to perform specific actions and complete tasks. They extend what an agent can do beyond just conversation. For example, an agent might use tools to:

• Search the internet for information
• Access and update customer records in a CRM
• Send emails or messages
• Schedule appointments
• Generate content or analyze data

Relevance AI provides both pre-built tool templates and the ability to create custom tools for your agents.

How does Knowledge for Agents work?

Knowledge in Relevance AI refers to the information and context provided to agents to help them perform their tasks effectively. This is often implemented through Retrieval Augmented Generation (RAG), which allows agents to access and use specific information sources when responding to queries or completing tasks.

By giving agents access to knowledge bases, you can ensure they provide accurate, up-to-date information specific to your business, products, or services.

What is a Multi Agent System (MAS)?

Yes, Relevance AI supports creating multi-agent systems where specialized AI agents work together to accomplish complex tasks. This is part of the AI Workforce feature, which provides a visual canvas where you can design, connect, and monitor teams of specialized agents.

How do agents handle situations they can't resolve?

Agents can be configured to escalate issues they can’t handle to human team members. For example, if an agent cannot answer a customer’s question, it can loop in a sales rep or manager via your preferred communication tool (email, chat, etc.). The human can provide an answer, which the agent can then use to respond to the customer and store for future reference.

What integrations are available for AI agents?

Relevance AI offers numerous integrations that allow agents to connect with external tools and services, including:

• Email platforms (Gmail, Outlook)
• CRM systems (Salesforce, HubSpot)
• Messaging platforms (Slack, WhatsApp, Telegram)
• Productivity tools (Google Calendar, Google Sheets)
• Knowledge management systems (Notion, Confluence)
• And many more

These integrations enable agents to access data and perform actions across your entire tech stack.

Can agents operate autonomously without human oversight?

Yes, agents on the Relevance AI platform can complete work end-to-end without human involvement. For example, you could create an agent that checks for new information daily and produces reports or updates websites automatically.

However, you can also configure agents to work in a co-pilot mode, where they assist humans rather than working completely independently. The best approach depends on your specific use case and comfort level with automation.

What are the system limits or quotas for AI agents?

Relevance AI has system quotas that define the maximum resource allocations for different aspects of the platform. These may include limits on the number of agents, conversations, knowledge bases, or API calls depending on your plan. Specific details about these quotas can be found in the system quotas documentation.

How do I monitor and improve my agents' performance?

Relevance AI provides tools to monitor your agents’ performance, including:

1. Task View: A centralized interface for monitoring, managing, and interacting with your AI workforce
2. Conversation History: Review past interactions to identify areas for improvement
3. Analytics: Track metrics related to agent usage and effectiveness

Regular monitoring helps you identify patterns, optimize agent behavior, and ensure they’re meeting your business objectives.

What is concurrency and how does it affect my agents?

Concurrency refers to the number of tasks that can be executed simultaneously by your agents. For more details, visit our System Quotas page.

How can I organize my Agents?

You can organize your Agents in several ways:

• Pin important Agents: Keep your most frequently used Agents at the top of your agents list in the main app for quick access
• Use folders: Organize Agents into folders based on purpose, department, or use case
• Project organization: Separate Agents across different projects based on your team structure

These organizational features help you manage large collections of Agents efficiently.

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