Agent

An AI model designed to autonomously interact with its environment to perform tasks, often adapting to new information.

What is an Agent?

An AI agent is a sophisticated system that can independently perform tasks, make decisions, and interact with its environment without constant human supervision. What sets agents apart from traditional AI models is their ability to perceive their environment, take actions based on that information, and adapt their behavior as circumstances change. These agents can handle complex sequences of tasks, learn from their interactions, and often work alongside other agents or humans to achieve specific goals.


In Lleverage's context, agents are fundamental building blocks in their visual workflow platform. Their platform enables businesses to create and orchestrate multiple agents working together in automated workflows, each specializing in specific tasks while contributing to solving complex business processes that traditionally required significant human intervention.

Why are Agents important?

AI agents represent a significant advancement in automation technology, enabling organizations to handle complex tasks that were previously too nuanced for traditional automation. Through Lleverage's platform, businesses can deploy agents to handle sophisticated processes while maintaining human oversight. This capability allows companies to automate knowledge work more effectively, reduce manual intervention, and scale operations more efficiently. The autonomous nature of agents means they can continuously work on assigned tasks, adapt to new situations, and maintain consistency in their operations.

How you can use
Agent
with Lleverage

A legal firm implements Lleverage's platform to automate document review processes. They create a workflow where one agent specializes in extracting key information from contracts, another compares this information against legal requirements, and a third generates summary reports. These agents work together autonomously, flagging only complex cases for human review, significantly reducing the time lawyers spend on routine document review while maintaining accuracy and compliance.

Agent
FAQs

Everything you want to know about

Agent

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What’s the difference between [Agent] and [regular AI Model]?

While traditional AI models typically perform specific, isolated tasks, agents are more autonomous and can interact with their environment, make decisions, and adapt their behavior based on new information. They can also maintain context across multiple interactions and work as part of a larger system.

How do agents coordinate in complex workflows?

Agents can be designed to work together in a coordinated manner, each handling specific aspects of a larger task. Through platforms like Lleverage, agents can pass information between each other, validate each other's outputs, and collectively solve complex problems while maintaining clear workflows and accountability.

More references for
Agent

Make AI automation work for your business

Lleverage is the simplest way to get started with AI workflows and agents. Design, test, and deploy custom automation with complete control. No advanced coding required.