Agent OS.
AI Agents

Meet the Agents

That Move Work Forward

Six specialized AI agents that research, design, sell, support, analyze, and automate — so your team can focus on what matters.

Explore All AgentsTalk to Sales

The Lineup

Six agents. One platform.Infinite leverage.

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Specialized Agents
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Tool Integrations
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Avg Accuracy
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Faster Than Manual

Agent Intelligence

How agents think. Four steps to intelligent action.

Every agent follows a consistent cognitive loop — perceive, reason, act, learn — getting smarter with every iteration.

01

Perceive

Agents observe triggers, messages, data changes, and user requests. They parse intent and extract the information needed to act.

Natural language understandingEvent detectionContext extraction
02

Reason

Using multi-step reasoning, agents plan their approach. They break complex tasks into sub-tasks and select the best strategy.

Chain-of-thought planningStrategy selectionRisk assessment
03

Act

Agents execute tasks using your tools and integrations. They read data, write outputs, send messages, and update systems in real time.

Tool executionAPI integrationsReal-time data access
04

Learn

After every task, agents store context, outcomes, and feedback. They get better at your specific workflows over time.

Outcome trackingMemory updatesFeedback loops
Intelligence

Adaptive reasoning. Not just pattern matching.

Each agent uses multi-step reasoning to break down complex tasks. They plan ahead, evaluate options, and adapt their approach based on intermediate results — just like an experienced team member would.

Chain-of-thought planning before execution
Dynamic strategy selection based on context
Self-evaluation and error correction loops
Confidence scoring on every output
Reasoning Trace
92% confidence
Analyze requestIntent classification
Plan approachMulti-step strategy
Execute tasks3 parallel actions
Verify outputQuality check
Context

Persistent memory across every interaction.

Agents remember past conversations, decisions, and outcomes. They build a richer understanding of your team, your preferences, and your workflows over time — no repeated briefings, no lost context.

Long-term memory that spans sessions
Working memory for active task context
Shared memory across agent boundaries
Automatic relevance ranking of past context
Memory Utilization67%
Long-term128 docs
Working24 active
Shared6 agents
Integrations

Connected to your tools. Not just talking about them.

Agents don't just describe what could be done — they do it. Direct API access to your stack lets them read data, write reports, send messages, update records, and push changes in real time.

500+ pre-built tool integrations
Custom API connectors via SDK
OAuth and API key management
Rate limiting and retry logic built-in
4 integrations active
💬
Slackconnected
🐙
GitHubconnected
📝
Notionconnected
📋
Linearsyncing
Teamwork

Agents that collaborate. Not just coexist.

When one agent finishes its part, it passes full context to the next. Research feeds into analysis, analysis feeds into action. Your agent team operates like a well-coordinated unit with shared goals.

Automatic context handoff between agents
Parallel execution with synchronization
Conflict resolution when agents disagree
Escalation paths for ambiguous decisions
Agent Handoff Chain
Research
Analysis14 docs
Analysis
Writer3 insights
Writer
Review—

The Evolution

Not one assistant. A team of agents.

See how Agent OS compares to traditional single-AI setups and disconnected agent teams.

Single AI

Single AI Assistant

  • General knowledge only
  • One conversation thread
  • Manual handoffs required
  • Limited context window
Team

Agent Team

  • Specialized skills per domain
  • Multiple parallel agents
  • Better accuracy on tasks
  • Separate, siloed contexts
OS

Agent OS

  • Shared persistent memory
  • Cross-agent collaboration
  • Unified workflow engine
  • Human approval gates
  • Full observability & audit
Get Started
Developer SDK

Build custom agents. Your logic, our infrastructure.

Use the Agent OS SDK to create agents tailored to your exact use case. Define behaviors, connect tools, set guardrails, and deploy in minutes — with full TypeScript support and enterprise-grade reliability.

Full TypeScript SDK with type-safe APIs
Custom tool definitions and API connectors
Configurable memory, reasoning, and guardrails
One-command deploy to managed infrastructure
my-agent.ts
import { Agent, Tool } from '@agent-os/sdk'

const agent = new Agent({
  name: 'analyst',
  model: 'claude-4',
  memory: 'persistent',
  tools: ['sql', 'slack', 'sheets'],
})

await agent.deploy()

Ready to build your agent team?

Start with one agent. Scale to an intelligent workforce.

Get StartedView Platform