The Operating System
for AI Agents
Memory, reasoning, permissions, tools, and execution — connected in one intelligent layer.
Architecture
Six Layers. One System.
Every layer works together to give agents the ability to reason, act, and stay accountable.
Memory Layer
Persistent, contextual memory that spans conversations, sessions, and agents. Every interaction builds a richer understanding of your workflows.
Reasoning Engine
Multi-step reasoning that plans, evaluates, and adapts. Agents don't just respond — they think through problems before acting.
Tool Execution
Direct integration with your tools and APIs. Agents read, write, query, and push data across your entire stack in real time.
Human Approval
Configurable approval gates that ensure humans stay in the loop. Define when agents can act autonomously and when they must ask.
Analytics
Full observability into agent behavior, decisions, performance, and resource usage. Every action is tracked and auditable.
Permissions
Granular access controls defining what each agent can see, touch, and modify. Role-based security at every layer of the system.
How It Works
From idea to production in four steps.
Go from concept to deployed agents in minutes, not months. Every step is designed for speed without sacrificing control.
Define Your Workflow
Start by mapping out what you need — triggers, agents, tools, and approval gates. Use our visual builder or the SDK to design multi-step flows.
Connect Your Stack
Plug in the tools your team already uses. Slack, GitHub, Notion, Salesforce, custom APIs — agents speak your stack natively.
Set Boundaries
Define what each agent can access, when it needs approval, and what data it can touch. Granular permissions at every layer.
Deploy & Monitor
Launch agents into production with full observability. Watch decisions in real time, review audit logs, and optimize performance.
Developer Experience
Build with code. Ship with confidence.
A fully typed TypeScript SDK, comprehensive REST APIs, and CLI tools that let you define, test, and deploy agent workflows entirely in code. No vendor lock-in, no black boxes.
import { Agent, Workflow } from '@agent-os/sdk';
const researcher = new Agent({
name: 'Research Agent',
tools: ['web', 'notion', 'slack'],
memory: true,
approval: 'on-send',
});
const flow = new Workflow({
trigger: 'slack.message',
steps: [researcher],
});
flow.deploy();
// → Agent deployed ✓Agent Lifecycle
Perceive. Reason. Act. Learn.
Every agent follows a continuous loop — receiving context, planning an approach, executing with precision, and improving from the result.
Perceive
Agents receive triggers from your stack — a Slack message, a webhook, a schedule firing. Context is loaded from memory and the current session.
Reason
The reasoning engine plans a multi-step approach, evaluates strategies, and selects the optimal path. Chain-of-thought is fully traceable.
Act
Agents execute against your tools — reading data, writing documents, sending messages, calling APIs. Each action is permissioned and logged.
Learn
Results are evaluated, memory is updated, and performance metrics are tracked. Every cycle makes the next one smarter.
Security & Compliance
Enterprise-grade trust. Built into every layer.
Security isn't a feature — it's the foundation. Every agent action is encrypted, logged, permissioned, and auditable.
SOC 2 Type II
Independently audited controls for security, availability, and confidentiality.
GDPR Compliant
Full data residency controls, right to erasure, and processing agreements.
End-to-End Encryption
AES-256 encryption at rest and TLS 1.3 in transit. Zero-knowledge architecture.
Role-Based Access
Granular permissions for every agent, user, and workflow. Least-privilege by default.
Audit Logging
Immutable logs of every agent decision, tool call, and data access with full context.
Data Isolation
Tenant-level data isolation with dedicated encryption keys and network boundaries.
Why Agent OS
The problem with AI agents today and how we solve it.
Most agent frameworks give you raw building blocks and wish you luck. Agent OS gives you a complete operating system — memory, reasoning, permissions, tools, and execution — so you can deploy agents that actually work in production.
Philosophy
Built forControlled Autonomy
Agents should be powerful enough to act on their own, but transparent enough that you never lose oversight.
Agents Can Act
Deploy agents that execute tasks end-to-end — from research to reporting, outreach to operations — without constant hand-holding.
Humans Stay in Control
Every workflow can include approval checkpoints. You define the boundaries; agents respect them unconditionally.
Every Action Is Logged
Full audit trail of every decision, tool call, data access, and output. Complete transparency at every level.
Every Workflow Can Require Approval
Set approval gates at any step. Critical decisions always pass through a human before execution.
See the Platform in Action
Experience intelligent agents running on a system built for trust, speed, and control.