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What Are Knowledge Agents?

Knowledge Agents are conversational AI assistants that combine knowledge, reasoning, and the ability to take action. They’re not just chatbots that answer questions - they’re collaborative partners that can help you get work done. Think of knowledge agents as building your own specialized AI assistant that:
  • Understands your specific domain or expertise
  • Converses naturally to understand what you need
  • Calls tools and workflows to actually accomplish tasks
  • Works iteratively with you to solve problems
  • Gets better as you train it with more knowledge
The key difference: Knowledge agents don’t just tell you how to do something - they can actually do it for you by invoking workflow agents and integrations.
Example: The Knowledge Agent Builder Assistant you see on Agent.AI is itself an knowledge agent! It helps you build knowledge agents by understanding what you want to create and can even invoke workflows to help set things up.

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Knowledge Agents vs Workflow Agents

Agent.AI offers two types of agents that work powerfully together:
AspectKnowledge AgentWorkflow Agent
InterfaceConversational chatStep-by-step workflow
How it worksAI-driven, adaptiveDeterministic, predictable
Best forUnderstanding + actionAutomation + tasks
ExecutionDecides what to doFollows exact steps
User interactionCollaborative dialogueInput → Run → Output
When to useComplex, varied requestsRepeatable processes

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The Power of Combining Both

The magic happens when knowledge agents invoke workflow agents as tools: 
User: "Find 10 tech companies in SF and enrich them with LinkedIn data"
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Knowledge Agent understands the request
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Calls your "Company Search" workflow agent
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Gets results, then calls "LinkedIn Enrichment" workflow
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Presents enriched data conversationally
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User: "Now save the top 5 to a Google Sheet"
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Knowledge Agent calls "Export to Sheets" workflow
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Done! User can keep iterating
This creates a natural, conversational way to orchestrate complex multi-step work.

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When to Use Knowledge Agents

Choose knowledge agents when you want to:

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Build a Personal Clone or Expert Assistant

Create an AI version of yourself or an expert in your domain:
  • Your personal assistant - Trained on your work, knows your processes, can execute tasks
  • Domain expert - Deep knowledge in a specific field (marketing, development, research)
  • Collaborative partner - Works iteratively with users to build/create something
  • Problem solver - Understands complex requests and orchestrates multiple tools
Example use cases:
  • Marketing strategist that can research, analyze, and create campaigns
  • Development assistant that understands your codebase and can run workflows
  • Research assistant that finds papers, analyzes them, and generates summaries
  • Sales assistant that researches companies and drafts outreach

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Create Interactive Tools

Build powerful interactive experiences:
  • Guided workflows - Conversational interface for complex processes
  • Data analysts - Ask questions about data, agent runs analysis workflows
  • Content creators - Collaborate on creating content across multiple steps
  • Report generators - Understand report requirements and orchestrate creation

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Orchestrate Multiple Workflows

Use knowledge agents as intelligent orchestrators:
  • Understand natural language requests
  • Decide which workflow(s) to run
  • Chain multiple workflows together
  • Handle variations in user requests
  • Iterate based on results

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When to Use Workflow Agents

Choose workflow agents when you need:
  • Automation - Scheduled or triggered tasks that run unattended
  • Predictable processes - Same steps every time, no variation needed
  • Backend tasks - No user conversation required
  • Integration pipelines - Connecting multiple systems
  • As tools - Called by knowledge agents to do the actual work!
The pattern: Build workflow agents for specific tasks, then create knowledge agents that intelligently decide when to call them.

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How Knowledge Agents Work

Here’s what happens when someone chats with your knowledge agent: 
User makes a request in natural language
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Knowledge Agent analyzes the request
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Searches knowledge base for relevant context
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AI decides what action(s) to take
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Calls workflow agents / tools as needed
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Processes results and responds conversationally
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User can iterate and refine
This creates an intelligent interface layer over your automations.

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Key Capabilities

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1. Knowledge Base

Train your agent with domain expertise:
  • Documents - PDFs, docs, research papers
  • Web content - Scrape websites and documentation
  • Videos - YouTube transcripts automatically extracted
  • Social content - Twitter/X threads, LinkedIn posts
  • Google Workspace - Docs, Sheets, Drive files
  • Direct input - Type or paste knowledge manually
The agent searches this knowledge to inform its responses and decisions.

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2. Tool Integration - The Real Power

This is where knowledge agents become truly powerful: A. Workflow Agents as Tools
  • Add any of your existing workflow agents as tools
  • Knowledge agent decides when to call them
  • Pass data between conversation and workflow
  • Chain multiple workflows together
  • Example: “Research agent” → “Enrichment agent” → “Output agent”
B. MCP (Model Context Protocol) Servers
  • Connect custom tools you build
  • Advanced developer capability
  • Extend agent capabilities infinitely
C. Composio Integrations
  • 100+ app integrations (Slack, Gmail, HubSpot, etc.)
  • Take real actions in external systems
  • Authenticate once, agent uses as needed

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3. Conversational Intelligence

Natural back-and-forth dialogue:
  • Context aware - Remembers conversation history
  • Clarifying questions - Asks when it needs more info
  • Multi-turn - Complex requests over multiple messages
  • Adaptive - Adjusts based on user feedback

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4. System Configuration

Define how your agent behaves:
  • System instructions - Guide personality and approach
  • Welcome message - Set expectations for users
  • Sample questions - Show what the agent can do
  • Prompt hints - Guide user input

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5. Conversation Management

  • Auto-titled - AI generates conversation titles
  • Searchable history - Find past conversations
  • Public sharing - Share conversations via link
  • Forking - Users can copy and continue shared chats

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Real-World Examples

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Personal Marketing Clone

What it does: Acts as your marketing expert, understanding strategy and executing tasks Configuration:
  • Knowledge: Your marketing playbooks, past campaigns, brand guidelines
  • Tools:
    • “Competitor Research” workflow agent
    • “Content Generator” workflow agent
    • “Social Media Poster” workflow agent
    • HubSpot integration for CRM
  • System prompt: “You are a marketing strategist. You understand our brand and can execute campaigns.”
Sample interaction: 
User: "Create a launch campaign for our new product feature"

Agent: "I'll help you create a comprehensive launch campaign.
Let me start by researching what competitors are doing...
[calls Competitor Research workflow]

Based on the competitive analysis, I recommend focusing on
[unique value props]. Should I draft the campaign content?"

User: "Yes, and schedule posts for next week"

Agent: "Great! [calls Content Generator workflow]
Here's the campaign content... [shows drafts]
[calls Social Media Poster workflow to schedule]
All set! 5 posts scheduled across LinkedIn and Twitter."

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Development Assistant

What it does: Understands your codebase and can run development workflows Configuration:
  • Knowledge: Your API docs, architecture decisions, coding standards
  • Tools:
    • “Run Tests” workflow agent
    • “Deploy” workflow agent
    • “Create PR” workflow agent
    • GitHub integration
  • System prompt: “You are a development assistant familiar with our codebase.”
Sample interaction: 
User: "I just pushed changes to the authentication module"

Agent: "Let me run the test suite to make sure everything passes...
[calls Run Tests workflow]

Tests passed! Ready to deploy to staging?"

User: "Yes, and create a PR for review"

Agent: [calls Deploy workflow for staging]
Deployed to staging ✓

[calls Create PR workflow]
PR created: #123 'Update authentication module'
Reviewers assigned based on CODEOWNERS.

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Research & Analysis Assistant

What it does: Conducts research and generates insights Configuration:
  • Knowledge: Your research methodology, data sources, analysis frameworks
  • Tools:
    • “Web Scraper” workflow agent
    • “Data Analysis” workflow agent
    • “Report Generator” workflow agent
    • Google Sheets integration
  • System prompt: “You conduct thorough research and generate actionable insights.”
Sample interaction: 
User: "Analyze the competitive landscape for AI agent platforms"

Agent: "I'll conduct comprehensive research. Let me start by
identifying key players... [calls Web Scraper workflow]

Found 15 competitors. Now analyzing their features and pricing...
[calls Data Analysis workflow]

Here are the key insights:
- [Insight 1]
- [Insight 2]

Should I generate a full report and save to Google Sheets?"

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Collaborative Content Creator

What it does: Works with you iteratively to create content Configuration:
  • Knowledge: Your brand voice, writing samples, content guidelines
  • Tools:
    • “Content Generator” workflow agent
    • “SEO Optimizer” workflow agent
    • “Image Generator” workflow agent
    • Google Docs integration
  • System prompt: “You help create high-quality content that matches our brand voice.”
Sample interaction: 
User: "I need a blog post about AI automation best practices"

Agent: "Great topic! Let me draft an outline based on our
content guidelines... [uses knowledge base]

Here's a proposed structure:
1. [Section 1]
2. [Section 2]
...

Does this flow work for you?"

User: "Perfect, write it and optimize for SEO"

Agent: [calls Content Generator workflow]
First draft complete! Now optimizing for SEO...
[calls SEO Optimizer workflow]

Added target keywords, meta description, and internal links.
Should I save this to Google Docs?

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Getting Started

Ready to build your powerful AI assistant?

Quickstart Guide

Build your first knowledge agent in under 10 minutes

Configure Your Agent

Set up system prompts, personality, and sample questions

Add Knowledge

Train your agent with domain expertise

Enable Tools

Give your agent the power to take action

Best Practices

Tips for creating effective knowledge agents

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Frequently Asked Questions

No! Knowledge agents are built using a no-code interface. If you can configure settings and upload files, you can build an knowledge agent. The platform handles all the AI complexity behind the scenes.
Knowledge agents give you:
  • Custom knowledge - Train on your specific domain
  • Action capability - Call workflows and integrations, not just answer questions
  • Tool orchestration - Intelligently chain multiple automations
  • Controlled behavior - Define personality and boundaries
  • Shareable - Public agents others can use
  • Integrated - Works with your Agent.AI workflows
Think of workflow agents as the “hands” (they do specific tasks) and knowledge agents as the “brain” (they decide what to do and orchestrate the hands). Knowledge agents call workflow agents as tools to actually get work done.Best practice: Build focused workflow agents for specific tasks, then create knowledge agents that intelligently decide when to call them.
Only through tools you enable. You can add:
  • Web search tools
  • Workflow agents that call APIs
  • Integrations that access external services
By default, they only know what’s in their knowledge base.
No, but they’re typically designed to be shared. You can:
  • Share publicly on the Agent.AI marketplace
  • Share specific conversation links
  • Keep completely private for your own use
Best practice: Don’t put sensitive/confidential information in public knowledge agents.
Add tools! Specifically:
  1. Build workflow agents for specific tasks (e.g., “send email”, “create report”)
  2. Add them as tools in the knowledge agent’s Action Agents tab
  3. Write good system prompts that tell the agent when to use each tool
  4. The knowledge agent will call these workflows when appropriate
See the Tools Integration guide for details.
Not directly, but you can create workflow agents that call knowledge agents via API, then have knowledge agents call those workflows. This creates powerful chains of AI reasoning and action.
Pro Tip: Start with a simple conversational agent, then gradually add workflow agents as tools. Test each tool individually before combining them. This iterative approach helps you build complex, powerful assistants reliably.