Merlin Agent Builder

What is an AI Agent?

An AI (Artificial Intelligence) agent is an autonomous system that can understand its environment's context, make decisions, and take actions to achieve specific goals. Unlike simple chatbots that only respond to questions, AI agents can:

• Understand context from multiple data sources
• Reason about problems using available information
• Take concrete actions through connected systems
• Learn and adapt their responses based on outcomes Think of it this way: While a chatbot might tell you "Your order status is unknown," an AI agent can check your order system, payment processor, and shipping provider, then either give you a complete status update or automatically resolve any issues it finds.

Components of an Agent on Tray

If you're familiar with building on the Tray platform, you can build an agent project that consists of:

• Agent scope - what you want your agent to do
  • Defines your agent's goals and behavior. This is critical for guiding the agent to successfully complete tasks. You provide relevant information to outline the agent's goals, specific instructions, and the style in which you want the agent to respond.
• Data sources - what information it can access
  • Connect your existing systems (Google Drive, Confluence, databases, etc.) to create a searchable knowledge base that your agent references when it needs context to make informed decisions.
• Workflows as tools - what actions it can take
  • Let your agent perform tasks by running chosen workflows, everything from running data queries to creating tickets to sending notifications. We provide prebuilt tools to help you get started, but you can also build your own bespoke tools using Tray's visual workflow builder.
• AI model - the brain that makes decisions
  • The LLM (Large Language Model) that powers decision-making. Your choice of model depends on your specific needs:
  • Task complexity - simple queries vs. complex reasoning
  • Response speed - fast responses vs. thorough analysis
  • Cost considerations - usage-based pricing varies by model
  • Context requirements - how much information the model needs to remember
• Agent workflow - how it all works together
  • This specialized Tray workflow acts as the orchestrator, using agent connectors to coordinate everything. It follows your scope guidelines, leverages your chosen AI model to understand requests and make decisions, searches your knowledge base for relevant information, and executes the appropriate tools to complete tasks. Each Tray agent is a Tray project where these components work together to deliver intelligent automation that understands your business context and takes real actions across your tech stack.