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.
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
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:- Start with clear objectives: Define specific tasks and goals for your agents
- Provide quality knowledge bases: Equip agents with comprehensive, up-to-date information
- Establish escalation protocols: Create clear paths for agents to involve humans when needed
- Monitor and refine: Regularly review agent performance and make adjustments
- Integrate with existing systems: Connect agents to your current tools and workflows
Frequently Asked Questions
Do I need coding knowledge to Invent an Agent?
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?
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
How does Knowledge for Agents work?
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)?
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?
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?
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
Can agents operate autonomously without human oversight?
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?
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?
How do I monitor and improve my agents' performance?
Relevance AI provides tools to monitor your agents’ performance, including:
- Task View: A centralized interface for monitoring, managing, and interacting with your AI workforce
- Conversation History: Review past interactions to identify areas for improvement
- Analytics: Track metrics related to agent usage and effectiveness