Multimodal DAG engine · Made by Digital Response

One brain for
every agent.

AgentsOS is the agentic operating system that plans, executes, and learns from complex workflows across software, cloud, AI, UX, architecture and business operations — in a single multimodal DAG.

Host locally, in your cloud, our cloud, or your own private cloud.

C4 CONTEXT DIAGRAM AgentsOS in your ecosystem
AgentsOS v3.1 · Bootable AI OS
Developer / CTO Governs · reviews
Mobile Dashboard Next.js · :3000
Telegram / WhatsApp Bot channels
Tailscale Secure remote access
GitHub Source · CI/CD
Actor System External

See the system think.

Every workflow becomes a live, inspectable DAG — orchestrated across a fleet of specialised agents, with Desky narrating the journey.

Master Orchestrator Live

Last updated: just now
+3
24
Active DAGs
live
18/20
Agents online
+12%
1,284
Tasks today
+0.4
98.6%
Success rate
Throughput
Mon
Tue
Wed
Thu
Fri
Agent load
Code Agent72%
Infra Agent48%
Vision Agent91%
Browser Agent33%
product-launch·deploy Code + Infra Running
fin-recon·q3 Docs Agent Done
visual-regression·web Vision Agent Running
iam-policy·audit Infra Agent Queued

Master Orchestrator

A single pane of glass over every running DAG. Track throughput, agent load and success rates in real time — with retries, fallbacks and concurrency policies applied automatically.

Agent Fleet

Six specialised agents — code, infra, vision, browser, Android and docs — each containerised, monitored and assigned by the resource engine based on modality, risk and cost.

Code Agent modality: code
142 tasks 72%
Infra Agent modality: infra
88 tasks 48%
Vision Agent modality: vision
61 tasks 91%
Browser Agent modality: web
37 tasks 33%
Android Agent modality: mobile
14 tasks 22%
Docs Agent modality: docs
96 tasks 55%

Desky — your project director

Desky sits on top of the orchestrator as a personified companion. It intakes briefs, explains plans, visualises DAGs, flags risks and summarises lessons learnt — in plain human language.

Desky Project Director · online

Desky, plan the launch of our new billing portal end-to-end.

On it. I've ingested the brief and built a Project Definition. Here's the execution DAG — 14 tasks across code, infra, visual QA and docs.

Brief
Plan
Code
Infra
IAM
QA
Docs

Looks good. What's the riskiest node?

The IAM policy migration carries the highest risk. I've queued a dry-run with rollback and a human approval gate before it executes.

Approval required
Ask Desky anything…

A complete lifecycle, from brief to lessons learnt.

Eight engines work as one — planning, orchestrating, executing and learning across every modality your business touches.

Brief ingestion pipeline

Natural-language intake turns unstructured briefs into structured Project Definition Objects with goals, scope, risks and constraints.

DAG task planning

Epics → stories → tasks with automatic dependency resolution, resource assignment and parallelisation.

Model autopilot

Local-first routing engine selects the optimal model per task — Ollama for cheap, cloud for complex, fallback on failure.

Multimodal DAG engine

Async DAG execution with node lifecycle, dependency resolution, retries and rollbacks across 6 modalities.

MCP tool marketplace

Plugin-based tool registry with versioning, sandboxing and access control — extend the platform without modifying core.

Memory OS

Graph + vector memory layer with OpenClaw. Every decision, every tool call, every failure is recorded in a provenance ledger.

Evolution & reflection

Genetic algorithms optimise DAG plans over time. The system learns which task decompositions produce the best outcomes.

Self-healing runtime

Watchdog monitoring, automatic container recovery, and persistent queues ensure the platform survives failures without data loss.

Five layers, one operating system.

UX Layer

MyDesk (Next.js) · Dashboard · Desky · Mobile · Telegram

Orchestration Layer

Master Orchestrator · DAG Engine · PDO Models · Evolution Engine

Agent Layer

Code · Infra · Vision · Browser · Android · Docs

Platform Layer

9Router · Model Manager · MCP Registry · Memory · Queue

Infrastructure Layer

Docker · Ollama · Qdrant · Neo4j · Redis · Tailscale

From the kernel to the corner office.

One multimodal engine spans technical orchestration and business orchestration — software, cyber, AI, design, architecture, automation, ops, finance and go-to-market.

Software & DevOps

CI/CD, code review, observability

codeinfrawebvision

Cloud & Cybersec

DNS, WAF, IAM, backups, compliance

infrawebvisiondocs

AI & Data

Model lifecycle, eval, data pipelines

codeinfravisiondocs

UI, UX & Product

Design systems, visual regression, usability

visionwebdocs

Enterprise Architecture

Catalog, impact analysis, governance

docsinfracodevision

Automation & RPA

Process mining, RPA, reconciliation

codeinfradocsvision

Your cloud, your rules.

Truly flexible deployment — from a single laptop to a Kubernetes cluster.

Self-Hosted

One-command install with Docker Compose. Single binary or full stack — runs on any Linux x86_64 host.

curl -fsSL https://agentsos.app/install.sh | bash

Cloud-Hosted

Managed AgentsOS in your cloud tenant. AWS, Azure, GCP — we deploy, secure and maintain the control plane.

agentsos cloud init --provider aws

AgentsOS Cloud

Fully managed SaaS. No infrastructure to manage — just submit briefs and get results. SOC 2 compliant.

docker pull agentsos/agentsos:latest

Give your business one brain for every agent.

Join the early access program. Be among the first to orchestrate your enterprise workflows with AgentsOS.

We'll review your application and get back to you within 48 hours