workspace(mode = "browser", ai = True)

No localhost. No servers. Just a browser.

def hero_headline(): font = "neue", weight = "semibold"

Edit Code Like a Document.
AI Is Your Teammate.

description = "browser-first IDE with AI copilot"

No localhost. No server setup. No toolchains. Open your browser and write infrastructure as code like an online document — with an AI copilot that codes alongside you in real time. No matter the scale or complexity.

No InstallBrowser-NativeAI Co-AuthorReal-Time Collab

Open Editor Login

‹›

app.reasonos.dev/workspace/acme-prod

acme-prod

Search Files

✦

Tools

TerminalOutputProblems

main2 people + AI

Ln 1, Col 1UTF-8RBS

rbs.ship(target = "prod", ai_assist = True)

Open a browser. Write code. Ship infrastructure. AI does the rest.

audit(toolchain) → 1000+ tools_detected1,000+tools in the average DevOps stack

consolidate(target = ["aws", "gcp", "azure"], platform = "rbs")

Stop Juggling Tools.
Ship to Prod & Multicloud.

cost_savings = 0.67 # ⅔ engineering spend

Replace your sprawling toolchain with one platform. Save ⅔ on your engineering spend with ReasonOS.

87avg. tools per company

→

1with ReasonOS

⅔engineering cost saved

Just you, your engineers, and AI.

onboard(friction = 0, enterprise = False)

Zero friction onboarding

create_repo(type = "mono-repo", git_hosting = "built-in")

Create a Repo.
Start Building.

No GitHub Enterprise required. No complex git hosting setup. Create a project directly in your browser — pick a template, name it, and you're coding with your team in seconds.

maina1b2c3d

Mono repos, build rules, or AI agents — one click

maine4f5a6b

Built-in git hosting — no third-party needed

devc7d8e9f

Instant dev environment — zero setup time

collabf0a1b2c

Invite your team and AI — collaborate from minute one

Create Your First Repo →

Create New Project

Build Rule

Extend RBS and create tools or make your tools available for other RBS (ReasonOS Build System) customers

Agent

Build voice agents or any agent with code. It's painful to build agents with low code — we make it easier and customizable with code

Mono repository

Your actual application repository. Organize your entire project structure in one place for better development workflow

PROJECT NAME

Enter project name

DESCRIPTION (OPTIONAL)

Enter project description

✦

#acme-platform👥4

Type a message...

📹

Video Meetings

Available

Infra Review👥 0

Start or join a meeting to collaborate in real time

create_meeting(name = "infra-review", mode = "windowed")

Built-in Collaboration

send_message(room = "#acme-platform", collab = True)

Chat. Meet.
Ship Together.

join_chat(channels = ["#general", "#infra", "#deploys"])

No Slack. No Zoom. No context switching. Chat with your team, hop on a video call, and share code — all without leaving the editor. AI joins your conversations, summarizes threads, and suggests code changes in real time.

Everything in one place

Team Chat

Channels for every project, PR, or topic. Share code snippets with syntax highlighting. AI auto-summarizes long threads.

📹

Video Meetings

Google Meet-style video calls with screen sharing. Start a meeting from any chat room — one click, no links, no apps.

👁

Live Presence

See who's online, what file they're editing, and their cursor position. Real-time awareness without interrupting.

✦

AI in Every Thread

AI reads the chat, understands context, and participates. Ask it to generate code, review diffs, or explain changes.

create_team(coordination = "hierarchical", context = "full-stack")

Hierarchical Agent Teams

spawn_teammate(role = "devops", context = ["code", "infra", "ci", "metrics"])

Spawn Teammates.
They See Everything.

send_message(type = "guidance", to = "InfraPlanner")

Every agent has full context over your code, infrastructure, CI pipelines, and observability — not just the file it's editing. A System orchestrator coordinates the team, issues guidance, and corrects agents in real time. When AI understands the entire stack, it ships code that actually works in production.

What agents can see

◆

Code

Every file, package, and dependency — agents review, edit, and refactor with full project context

◆

Infrastructure

Cloud configs, Kubernetes clusters, networking — agents provision and deploy knowing the full topology

◆

CI / CD

Build rules, test targets, pipelines — agents run tests and gate deploys automatically

◆

Observability

Logs, metrics, traces, uptime — agents detect issues and fix them before users notice

✦Agents get smarter every run

Every correction, every pattern discovered, every architectural decision — agents persist what they learn to memory. The next time they encounter the same problem, they already know the answer. Your team's accuracy compounds over time.

Run 1→72% accuracy

Run 10→91% accuracy

Run 50→99% accuracy

👥Agent Team0 agentshierarchical

⊞⊟≡

⇌Message Bus0 messages

Waiting for messages...

native.products(visibility = "public")Products

The Operating System for
Intelligent Engineering + DevOps Automation

We manage your entire stack – single or multi-region – beyond basic servers and databases. Seamless synchronization, no complex Terraform required. Deploy with confidence, at any scale

kubernetes(providers = ["aws", "google", "azurerm"])

ReasonOS for Cloud Development

One .rbs file provisions infrastructure across every cloud. No Terraform modules, no CloudFormation stacks — just declare what you need.

Start building →Read our blog →

infra.rbs

1PROVIDERS = ["aws", "google", "azurerm"]

3cluster = kubernetes(

4 name = CLUSTER_NAME,

5 version = "1.29",

6 providers = PROVIDERS,

7 node_pools = [

8 { "name": "default", "min": 2, "max": 10 }

9 ],

10 enable_logging = True,

11 enable_monitoring = True,

12)

$ rbs apply infra.rbs

→ Provider: aws, google, azurerm

→ Creating cluster "acme-prod-k8s" (v1.29) ...

✓ 3 clouds • 6-30 nodes • logging + monitoring on — 48s

AWS

Google Cloud

Azure

context_engine(scope = ["code", "infra", "ci", "observability"])

AI That Sees Your Entire Stack

Your code, infrastructure, CI pipelines, and production metrics — all in one graph. When AI has full context across every layer, it makes decisions a siloed tool never could.

See AI in action →

rbs context-engine

◆

Code✓

1,247 files • 38 packages • 4 languages

◆

Infrastructure✓

infra.rbs • 3 clouds • 12 services • k8s v1.29

◆

CI / CD✓

BUILD.rbs • 6 pipelines • 412 test targets

◆

Observability✓

Logs • Metrics • Traces • 99.97% uptime

✦ Unified context graph — every layer connected

[SCAN] Indexing code, infra, pipelines, metrics...

[GRAPH] 1,247 files → 38 packages → 12 services → 3 clouds

[LINK] CI targets linked to infra + observability

✓ Full-stack context active — AI sees everything

ai_agent(mode = "devops", auto_deploy = True)

Augmenting and Enhancing DevOps

Tell the AI what you need in plain English. It writes the .rbs config, provisions infrastructure, runs tests, and deploys — you review the diff.

See automation →

RBS AI Agent

acme-prod workspace

Deploy the frontend to staging with a canary rollout at 10%

✦ Reading BUILD.rbs and infra.rbs...

Generated deploy_staging.rbs:

canary_deploy(

target = "//client/apps/shell",

env = "staging",

canary_weight = 10,

)

✓ Build passed — 14s

✓ 142 tests passing

✓ Canary deployed — 10% traffic routed

✦ Staging canary live. Monitoring error rate — promote to 100% when ready.

testimonials(verified = True, count = 3)Customer Stories

Trusted by engineering teams
building the future

"ReasonOS transformed our DevOps chaos into elegant simplicity. One .rbs file now manages our entire multi-cloud infrastructure - what used to take weeks of coordination across teams now happens in minutes."
Highlighted ReasonOS features
Multi-cloud automationDSL-driven deploymentTool consolidation
Use case
Construction ERP platform

"Before ReasonOS, we had 15+ DevOps tools and constant configuration drift across AWS, GCP, and Azure. Now everything is unified in one platform with perfect consistency. Our deployment confidence went from 60% to 99%."
Highlighted ReasonOS features
Cross-cloud consistencyConfiguration managementAutomated scaling
Use case
Sleep health monitoring platform

"The AI-powered context engine is revolutionary. ReasonOS understands our infrastructure intent and suggests optimizations we never considered. It's like having a senior architect reviewing every deployment."
Highlighted ReasonOS features
AI-powered insightsSmart optimizationIntelligent automation
Use case
Research computing

rbs.get_started(plan = "enterprise", trial = True)

Explore ReasonOS today

Talk to one of our experts →Read our blog →

Edit Code Like a Document.AI Is Your Teammate.

Stop Juggling Tools.Ship to Prod & Multicloud.

Create a Repo.Start Building.

Video Meetings

Available

Chat. Meet.Ship Together.

Spawn Teammates.They See Everything.

The Operating System forIntelligent Engineering + DevOps Automation

ReasonOS for Cloud Development

AI That Sees Your Entire Stack

Augmenting and Enhancing DevOps

Trusted by engineering teamsbuilding the future

Highlighted ReasonOS features

Use case

Highlighted ReasonOS features

Use case

Highlighted ReasonOS features

Use case

Explore ReasonOS today

Edit Code Like a Document.
AI Is Your Teammate.

Stop Juggling Tools.
Ship to Prod & Multicloud.

Create a Repo.
Start Building.

Chat. Meet.
Ship Together.

Spawn Teammates.
They See Everything.

The Operating System for
Intelligent Engineering + DevOps Automation

Trusted by engineering teams
building the future