Deployment.io

You describe the outcome.Our AI agents write the code and ship it.

Planned across your repos, verified before you review, and deployed to your cloud.

Describe a feature, a migration, or a fix. You approve what reaches production.

From outcome to production

STEP 01

You describe an outcome

A prompt or a backlog item — “Add a health check to every service.” The planning agent reads your repos and plans the change across every affected service.

Auto-playing — tap a stage to explore
app.deployment.io

The planning agent turning one outcome into a coordinated plan across your repos.

Native MCP server + open-source skill — works with the agents you already use

Claude CodeCursorWindsurfGitHub CopilotOpenAI CodexGemini CLI

How the work flows

Context, then a plan, then agents doing the work.

The same three steps a good engineer takes: understand the system, agree on what needs to be done, then build it.

1 · Context2 · Assistant3 · Tasks

1 · Context

Your agents start with your system, not a blank repo.

Before anyone writes a line of code, Deployment.io builds a shared picture of your org: every repository, every environment and database, everything actually running in your cloud, and which repo ships each piece of it.

Every repo in your org
Connect GitHub, GitLab, or Bitbucket once and the catalog builds itself — languages, services, and entry points included.
What's actually running
The scan happens from inside your own cloud: environments, services, databases. Your credentials never leave your account.
The agent knows which repo owns what
It won't go editing the wrong service because two repos have similar names. Where it isn't sure, it asks instead of guessing.
Corrected once, reused forever
Fix a low-confidence guess and it sticks. Every session and every task afterwards starts from the corrected answer.

It refreshes on demand, so it never quietly drifts out of date.

ContextBuilt 12 min ago
24
Repositories
6
Environments
3
Databases
18
Services running

Service → repo

  • checkout-apiacme/checkouthigh
  • billing-workeracme/billinghigh
  • notify-svcacme/platform?low

Low-confidence matches wait for a human to confirm them — once.

2 · Assistant

Think it through before anything gets built.

Start a session and you're talking to an agent that has already read the relevant repos. It asks the questions a senior engineer would ask instead of guessing — and turns the conversation into a spec you can actually hand off.

Think out loud without risking anything
A session only reads and discusses. Nothing you explore becomes a branch, a commit, or a pull request until you decide it should — so you can chase a bad idea for ten minutes and lose ten minutes.
Catch the vague request before it costs you a day
The conversation becomes a written spec: the goal, what counts as finished, what's off the table. You find out the ask was ambiguous now, not after an agent spent an afternoon building the wrong thing.
Never locked to one model
Plan with one, build with another. When a better coding model ships next quarter, point the work at it — nothing to rewire, and you can bring your own provider key.

When the spec reads right, convert it — it lands in the Tasks backlog as a draft, ready for whoever starts it.

SpecSession · Claude Code
ReadyComplexity: medium3 repos

Goal

Move session auth onto rotating refresh tokens without logging anyone out.

Acceptance criteria

  • Existing sessions stay signed in through the cutover
  • Refresh tokens rotate on every use
  • Rate limit is enforced per user, not per IP

Out of scope

SSO, password reset emails.

Convert to Task→ lands in Backlog

3 · Tasks

A board your team shares with its agents.

The same board you'd use to track work with people — except the assignee is a coding agent. Drop a card in the backlog, pick who runs it, and watch it move to done.

TasksBoard
Backlog2

Rotate refresh tokens

Opus 4.8

Drop legacy /v1 routes

GPT-5.5
Pending1

Add SBOM to release

Sonnet 4.6
Running1

Node 18 → 20, all services

Opus 4.8live
Done2

Fix flaky checkout test

GPT-5.3PR #412

Cache invalidation bug

Haiku 4.5PR #409

Every card runs in an isolated container in your cloud and ends as a pull request you review.

Assign work to an agent, not a person

Match the model to the job: something cheap for a dependency bump, something strong for a migration. Claude Code, Codex, or your own provider key.

Your code never lands on our infrastructure

Every task runs walled off inside your own AWS account. Your code, your secrets, and your build artifacts stay there — we never hold a copy.

Lands in the workflow you already have

Every task finishes as a pull request in your repo, so your existing review, CI, and branch rules just apply. Nothing new for the team to adopt.

Approvals stay with your team

Tool calls that need permission queue up for a human. Nothing reaches production without a sign-off.

What our agents ship

First-class support for the workloads teams actually run in the cloud.

Static Sites

Our agents ship React, Next.js, Vue, and other static sites with HTTPS, a global CDN, cache invalidation, and rollbacks built in.

e.g., “Migrate our docs from Hugo to Astro and ship it.

Web Services

Go, Node.js, Python, Ruby, and Rust services deploy with auto-scaling, health checks, and zero-downtime rollouts.

e.g., “Bump Node from 18 to 20 across all services and roll out.

Multiple Environments

Stand up dev, staging, and production environments — each in its own cloud account if you want. Our agents deploy to any of them.

e.g., “Stand up a staging environment for the checkout-v2 branch.

The platform underneath

Built for agents. Controlled by you.

The features that make agent-led deploys safe, fast, and predictable.

Native MCP tool surface

Agents call real deploy actions over MCP. Not chat — actual deploys.

Zero-config auto-detection

Our agents read your Dockerfile, port, health check, and build command from the repo. No YAML.

Human approval gates

Production deploys pause for sign-off. Approve from Slack or the dashboard.

RBAC for humans and agents

Scope what each teammate and each MCP token can deploy, read, or approve.

Auto-deploy on git push

Wire a branch to an environment once. Every push triggers a deploy.

Custom domains, HTTPS, Slack alerts

Bring your domain. Certs, CDN, and load balancing wired automatically. Alerts in Slack.

Security & control

Your cloud. Your data. By architecture, not promise.

Deployment.io runs inside your own cloud. We don't proxy your traffic, store your code, or hold your secrets.

Read the full security model

Your cloud, your data

Code, secrets, build artifacts, and runtime traffic never leave your cloud.

Open-source runner

The runner that touches your infrastructure is open source. Audit it, fork it, run your own build.

Revoke access anytime

We connect via a scoped role you control. Detach the role and we lose all access — instantly.

Approval gates by default

Production deploys require human approval. Role-based access controls scope what each teammate (and each agent) can do.

Ship outcomes. Keep the keys.

Describe what you want. Every change is tested before you review it; every production deploy waits for your sign-off.