AI Agent Network
Your autonomous knowledge workforce
Beyond Chat — Autonomous Intelligence
ATLAS doesn't just store knowledge. It deploys six specialized AI agents that work autonomously on your behalf.
These agents aren't chatbots. They're workers with specific roles, capabilities, and outputs.
The Agent Squad
🔬 Researcher Agent
Role: Deep investigation and analysis
The Researcher takes a topic and produces comprehensive analysis:
Searches across your knowledge graph
Identifies relevant concepts and content
Synthesizes findings into structured reports
Highlights knowledge gaps
Output: Research reports with citations to your own knowledge
📚 Curator Agent
Role: Knowledge organization and quality
The Curator maintains your knowledge graph health:
Identifies duplicate or overlapping concepts
Suggests merges and reorganizations
Scores content quality
Recommends archival or deletion
Output: Curation recommendations and quality scores
📝 Reporter Agent
Role: Content generation and synthesis
The Reporter transforms knowledge into outputs:
Generates summaries and digests
Creates newsletters from recent additions
Produces topic-specific briefings
Writes content drafts
Output: Ready-to-publish content pieces
⚡ Executor Agent
Role: Action management and completion
The Executor works through your action queue:
Prioritizes pending actions
Researches background for tasks
Suggests next steps
Tracks completion status
Output: Prioritized task lists with context
🧠 Memory Agent
Role: Retrieval and recall
The Memory Agent handles intelligent retrieval:
Answers questions about your knowledge
Finds relevant prior content
Surfaces forgotten insights
Provides contextual recall
Output: Precise answers with source citations
🛠️ Builder Agent
Role: Project execution (BUILDR ZONE)
The Builder turns ideas into implementations:
Takes project briefs from your knowledge
Produces code, documents, or artifacts
Iterates based on feedback
Delivers completed outputs
Output: Working implementations and artifacts
How Agents Work
Context Injection (Not Tools)
Unlike typical AI assistants that call external tools, ATLAS agents receive pre-loaded context from your knowledge graph:
This means:
Faster responses — No round-trip tool calls
Better coherence — Full context available from start
Lower cost — Efficient context window usage
Agent Orchestration
Agents can work independently or coordinate:
Solo Mode: Single agent handles a task
Squad Mode: Multiple agents collaborate
Agent Capabilities
Knowledge Tools
search_knowledge
Full-text search across your graph
explore_graph
Traverse concept relationships
get_concepts
Retrieve specific concepts
get_actions
Access action queue
get_insights
Retrieve insights by topic
Web Tools
web_search
Search the broader internet
fetch_url
Retrieve web content
File Tools
read_file
Access local files
write_file
Create outputs
list_directory
Navigate file systems
Agent Outputs
Research Report Example
Running Agents
Via CLI
Via API
Via Dashboard
Click the "Agents" tab and select which agent to run with your parameters.
Privacy & Control
Local First
Agents run on your infrastructure. Your knowledge never leaves your machine unless you explicitly expose it.
Audit Trail
Every agent action is logged:
What agent ran
What context was used
What output was produced
When it happened
Control Parameters
You decide:
Which agents can access which knowledge
How much context agents receive
Whether outputs are auto-published or reviewed
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