Introduction
The Build Overview gives you a complete picture of how to create, configure, and launch Agents inside Arahi AI.
Each Agent is made up of modular building blocks — prompts, tools, triggers, memory, variables, and integrations — that work together to automate complex workflows.
This page will help you understand what each part does and how they interact so you can design powerful, reliable Agents that perform like human specialists.
What Makes Up an Arahi AI Agent
Component | Purpose | Example |
|---|---|---|
Prompt | Defines the Agent’s role, behavior, and goal. | “Summarize new research papers and extract key insights.” |
Tools | Gives the Agent real-world capabilities — connecting to APIs, CRMs, files, or databases. | “Send email”, “Search docs”, “Update Notion” |
Triggers | Determine when and how an Agent runs. | “New lead created in HubSpot” |
Escalations | Define what happens when an Agent needs human help. | “Flag to team if customer sentiment is negative.” |
Memory | Allows the Agent to remember context or history. | “Remember last 5 customer interactions.” |
Variables | Store reusable values to make the Agent flexible. | “{{company_name}}”, “{{priority_level}}” |
Integrations | Connect Arahi AI to your tools and apps. | Slack, Google Drive, CRM, Webhooks |
Build Process in Arahi AI
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Start a new Agent
Go to your Agent Builder → click “New Agent.”
Give your Agent a name, description, and purpose. -
Design the Prompt
Define the Agent’s role and behavior clearly.
Example: “You are a Marketing Strategy Agent that generates personalized campaigns based on the target customer profile.” -
Add Tools
Attach built-in or custom tools (e.g., document parser, data enricher, Slack poster).
Each tool performs specific actions when called by the Agent. -
Set Triggers
Configure when your Agent should act — automatically via events, on a schedule, or manually. -
Define Escalation Logic
Specify conditions where the Agent should hand off to a human or alert a manager. -
Enable Memory and Variables
Add short-term or long-term memory to give the Agent context retention, and define variables for dynamic customization. -
Integrate External Apps
Connect with your workspace apps (CRMs, project tools, data stores, APIs). -
Test, Debug, and Deploy
Run test scenarios, review logs, and refine prompts or tool configurations.
Once ready, switch the Agent from Draft to Live.
Visualizing the Flow
An Arahi AI Agent follows this lifecycle:
This ensures every automation runs predictably and remains auditable.
Best Practices
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Start with clarity: Define a single outcome per Agent before expanding capabilities.
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Iterate quickly: Test small workflows and refine before scaling.
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Document your tools and triggers: Helps maintain clarity as your Agent network grows.
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Monitor performance: Use Arahi AI analytics to track success rates, escalation frequency, and automation ROI.
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Stay compliant: If your Agent processes customer or personal data, follow your organization’s GDPR/SOC 2 policies.