Deploy it · Run it · Trust it

Deploy and run any workflow or automation. It's that simple.

Drop your Python script. Snapdock runs it in the cloud 24/7 — no servers, no Docker — and tells you in plain English the moment it breaks.

No servers. No Docker. No YAML. — no DevOps required.

Bring Python from any LLM. No card to start.

Running automations for clients? Become a Founding Partner

Drop it in — watch it deploy and run.

Upload your code or drag a file here · .py · .zip · a whole project
Reading your code…
✓ Deployed in 1.4s · detected data sync · runs every morning
Ran your automation — finished in 4.2s
› synced 42 records · wrote results.csv · emailed you
Run this for real →

Built it with AI? Snapdock deploys & runs it — bring Python from

ChatGPT Claude Gemini Grok DeepSeek Llama Mistral Perplexity

What is Snapdock?

Snapdock is a cloud platform that deploys and runs your Python scripts and automations — on a schedule, 24/7, with no servers or Docker — and explains every run in plain English.

  • Category: deployment & operations for AI-built automations
  • Runs: backend Python — scheduled scripts, syncs, reports, routers, jobs
  • Setup: none — no servers, Docker, YAML, or terminal
  • Watches: every run; plain-English alert the moment one fails
The problem

Building it with AI was easy. Running it 24/7 isn't.

You built it to run without you. On your machine, it did — then reality set in. Three things every builder runs into:

“It only runs when my laptop's open.”

A script on your desktop or a half-forgotten cloud box. Nothing runs it reliably on a schedule, and nothing shows you it's still going.

“When it breaks, I get a stack trace I can't read.”

An LLM wrote the code; you didn't. Decoding a traceback isn't your job — so a small break costs an afternoon.

“I found out it broke from someone else.”

No alert fired. The way you learn a job stopped is the way you dread — after the report didn't land.

If you built it, Snapdock runs it

Syncs, reports, routers — running on their own.

Drop in your Python — a script or a whole project. We deploy it, schedule it, and explain every run in plain English.

Scheduled jobs & syncs

Recurring Python that pulls, transforms, and moves your data — on time, off a cloud machine, not your laptop.

Reports & reconciliations

The numbers job that has to be right — run on schedule, summarized in plain English, with its files a click away.

Routers & workflows

New-lead routers, notifiers, and the glue between your tools — the Python you generated, running unattended.

How it works

Ninety seconds. No terminal in sight.

No YAML either. Four steps, and it deploys, runs, and explains itself.

1

Drop in the code.

Upload a .py, a .zip, or a whole project. Snapdock finds the entrypoint, reads your dependencies, and quietly fixes the Windows-to-Linux gotchas so it just runs.

Detected entrypoint main.py · 4 dependencies · fixed line endings & paths automatically.
2

We check it, then deploy it.

A plain-English pre-flight flags anything that would bite — hardcoded keys, missing packages — and auto-fixes what it can. Then it deploys to the cloud, pre-warmed. Nothing to keep open.

Heads up: API_KEY is hardcoded — move it to the Secrets vault?  [ Add to vault ]  [ Deploy ]
3

Pick a schedule.

Every morning, hourly, weekdays at 9 — a preset or your own cron. From then on it runs on time, on its own, independent of any server staying up. Pause, resume, or run it now whenever.

Run every day at 9:00am?  [ Schedule ]
4

Read what happened — in a sentence.

After every run, a plain-English summary of what your automation actually did — not just what it printed. Any files it produced — CSV, XLSX, PDF — are right there to download.

Synced 42 records, wrote results.csv, emailed you@work.com.  ·  09:00 · 4.2s
For agencies

Run automations for clients? Earn on every one.

Run all your clients' automations on one account and earn a lifetime share on every one — even after a client starts paying their own card. You're the reseller, not the referrer.

The facts

What Snapdock does — and what it doesn't.

Plain, checkable capabilities. No “best” or “#1” claims — just what's true today.

CapabilitySnapdockNotes
Deploy & run backend Python from any LLMYesChatGPT, Claude, Gemini, and others — as-is
Run on a schedule, 24/7, off a cloud machineYesPresets or your own cron
Plain-English summary of every runYesWhat it did, not just what it printed
Plain-English failure alert + likely fixYesEmail, Slack, or Teams, with one-click re-run
Encrypted secrets vault, versions & rollbackYesKeys injected at runtime, never logged
Dockerfile, YAML, or a terminalNever neededAuto-detected — drag the folder in
Host front-end web apps (React / Next.js)NoUse Vercel or Netlify for front-ends
Credit card to startNoNo card to start

Capabilities reflect what's live today; comparison pages describe the fuller roadmap.

It runs your automations. And tells you everything.

One calm summary of every run. No noise, no 2am pages.

Plain English, not logs

Every run explained in a sentence. When one fails, Snapdock flags the problem in a sentence — not a stack trace.

It sees what it actually did

Not just what your code printed — the effect at its edges: “created 9 contacts, posted 14 messages.” No SDK to add.

Runs on its own

Scheduled runs fire on time, independent of any server staying up. Deploy once and stop thinking about it.

Secrets stay secret

Store API keys in an encrypted vault, injected at runtime. Keys never sit in your code or your logs.

Versions & rollback

Re-upload a new version anytime. If something's off, roll back to the last good one in a single click.

Share a run

Send anyone a clean public page of a run — the plain-English summary and every downloadable output file.

When a run fails

A sentence, not a stack trace.

Snapdock turns the error into plain English, points to what broke, and hands you a likely fix — then pings you by email, Slack, or Teams with a one-click re-run.

● It failed

What broke, and a fix to paste.

No traceback to decode. Snapdock reads the error, tells you what happened, and drafts the fix — ready to paste back into your LLM and re-upload.

Summary

stripe-export couldn't fetch charges at 2:14am.

What happened

Your Stripe API key has expired. Add a fresh key to your Secrets vault and re-run.

Likely fix

STRIPE_API_KEY → add a fresh key in Secrets, then re-run
● It worked

What it did, in plain English.

Every successful run gets the same treatment — a one-sentence summary of what actually happened at its edges, plus any files it produced.

Summary

lead-sync synced 42 records and wrote results.csv.

Output files

results.csv · 12 KB  ·  report.pdf · 88 KB

Workspaces

Workspaces that grow with you.

Organize automations into workspaces, invite the people who need to see them, and keep each project's work cleanly apart — all on one login.

Solo now, team later

Start solo. Add people free.

Run everything on your own login today. Bring in a collaborator — or give a client access — whenever you need to. Members are free, so growing never adds a per-seat bill.

For teams

Roles, handoffs, one login.

Set owner or member roles, switch between workspaces from the sidebar, and hand off ownership cleanly when someone moves on — the whole team on a single login.

Stay organized

A workspace per project.

Keep each project's automations in their own workspace, switch from the sidebar, and see every automation — what ran, what's healthy, what needs you — on one dashboard.

Where each tool fits

Built for people who shouldn't have to read a stack trace.

All good tools — for engineers. Snapdock is for the builder who just needs the Python an LLM wrote to deploy, run, and explain itself. Here's where each fits:

vs. cloud & compute platforms

Reach for them when you want hands-on control of infra. Snapdock, when you never want to open a terminal — it runs the code and explains it in plain English.

vs. visual / no-code tools

Reach for them when your logic fits prebuilt blocks. Snapdock, when you already have real Python from an LLM and don't want to rebuild it as a drag-and-drop graph.

vs. engineer observability

Reach for them when engineers need metrics and traces. Snapdock, when you need a plain-English answer to “did it run, what did it do, and why did it break?”

Pricing

No card while we're in early access.

No card, no call. Bring your automations now — paid plans are a flat monthly price by how many you keep running (Starter $49, Pro $199, Scale $499). Members are always free.

FAQ

The questions you're already searching.

Why does my AI-built app stop when I close my laptop?+

Because it only runs while your machine is on. A script on your laptop — or a browser tab — dies the moment you close the lid or lose Wi-Fi. Snapdock runs it on a cloud machine instead, so it keeps going 24/7 whether or not your computer is on.

Do I need Docker to deploy an AI-built automation?+

No. Snapdock auto-detects how your Python runs and its dependencies — there's no Dockerfile, YAML, or build config to write. Drop in a .py, a .zip, or a repo and pick a schedule.

How do I keep a Python automation running 24/7?+

Upload the script to Snapdock and choose a schedule (every morning, hourly, weekdays at 9, or your own cron). Snapdock runs it on a cloud machine on time, independent of any server or your laptop staying on, and watches every run.

Can I run the Python that ChatGPT, Claude, or Gemini wrote for me?+

Yes. Snapdock is builder-agnostic — bring Python generated by any LLM. Drop it in as-is; Snapdock detects how it runs, deploys it, schedules it, and explains every run. No rewrites.

Does Snapdock host front-end web apps?+

No. Snapdock runs backend Python workflows and automations — scheduled scripts, syncs, reports, routers, and jobs. For a front-end website or single-page app, use a static host like Vercel or Netlify; point it at Snapdock for the automation behind it.

What happens when a run fails?+

Snapdock turns the error into a plain-English sentence, points to what broke, and hands you a likely fix — then notifies you by email, Slack, or Teams with a one-click re-run. A sentence, not a stack trace.

Get started

Deploy and run any workflow or automation.

Start now. Your first automation is deployed and running in minutes — no servers, no Docker, no YAML.

No card to start, no call.