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Your hardware · your models · your data

Sovereign AI
starts at your desk

A complete AI development environment on your own machines: notebooks, your GPUs and your models, and a cluster to try what you build, all driven from a coding agent. Models, components and services load and unload as you need them, so your machine's limited resources go to the work you are doing now.

  1. Get models
  2. Fine-tune
  3. Build apps
  4. Evaluate
How you work

Every task is a sentence to your agent

Thinkube is designed for you to work from a coding agent. The platform gives the agent its own tools for every part of it: when you ask, it sees which models are loaded, what each GPU is holding, how a deploy is going and what a service logged, and it runs the same operations you would run by hand. You decide what happens: the agent changes something only when you ask. Every playbook on this site starts with the sentence to say.

Four areas, one platform

Playbooks

First time here?

All playbooks

Thinkube Kubernetes 30 min

Check and restart services from your agent

beginner

Ask what is running and whether it is healthy, restart a service, and turn one off and on again, from a chat with your agent

2026-10-04
Thinkube Kubernetes 30 min

Install and remove optional components

beginner

Add a database, a vector store or an inference backend to the platform when you need it, and take it out again

2026-10-04
Thinkube GitOps 30 min

Build a web app from the template

beginner

A full-stack app with a database and a login, at its own address, from one sentence

2026-10-04
Thinkube GitOps 30 min

Change your app and ship it

beginner

Edit the code, run its tests, push, and the new version is live

2026-10-04
Thinkube GitOps 30 min

Pass configuration to your app

beginner

Values your app reads at run time, and the few the browser may see

2026-10-04
Thinkube GitOps 30 min

Publish your app as a template

beginner

Turn an app you improved into a template anyone on your cluster can deploy

2026-10-04
Thinkube GitOps 30 min

Run a pipeline from your app

intermediate

Multi-step jobs your app submits and Argo Workflows runs, each step in your app's own image

2026-10-04
Thinkube GitOps 30 min

Deploy a serverless service

beginner

A service that runs only while it is being called, like AWS Lambda, on your own machines

2026-10-04
Thinkube GitOps 30 min

Store and fetch files with the file gateway

beginner

Upload, list, download and delete files in Thinkube Storage over a REST API and a web page

2026-10-04
Thinkube GitOps 30 min

Convert papers to Markdown and JATS XML

intermediate

Turn PDF papers into structured text with Docling, on CPU in a pipeline step or with a vision model on your GPU

2026-10-04
Thinkube Models 30 min

Serve your first model

beginner

Load an open model on your own GPU and call it from a notebook, as you would call a cloud API

2026-10-04
Thinkube Models 30 min

Load a model on the node and context you choose

intermediate

Pick the GPU node, the backend and the context length for a load, and what happens when a node is busy

2026-10-04
Thinkube Models 30 min

Call your models from an app or a script

beginner

Point the OpenAI or Anthropic client you already use at your gateway, with a Thinkube API token

2026-10-04
Thinkube Models 30 min

Build a notebook environment

beginner

Start from agent-dev or fine-tuning, add the packages you need, and get a kernel built for every architecture in your cluster

2026-10-04
Thinkube Models 30 min

Run notebooks from your agent, watched or unattended

beginner

Have your agent run a notebook while you watch it in a Thinkube IDE tab, or on a server of its own that stops when the run ends

2026-10-04
Thinkube Models 30 min

Build a research assistant over your papers

intermediate

Index arXiv papers in your own vector store, ask questions that come back with sources, and let agents argue from the index

2026-10-04
Thinkube Models 9 h 30 min

Fine-tune a model on rewards a program checks

advanced

Train a 4B model with GRPO against a solver that grades every answer, with no labelled data, and register the result beside its run

2026-10-04
Thinkube Models 30 min

Serve a model you fine-tuned

intermediate

Give a registered fine-tune a catalogue entry, load it on a GPU and call it through the gateway like any other model

2026-10-04
Thinkube Tandem 2 h

Serve the model Thinkube Tandem Chat uses

beginner

Mirror and load the model behind the gateway alias thinkube-fast, then ask your first question in a Thinkube Tandem Chat

2026-10-04
Thinkube Tandem 1 h

Build your first application change with Tandem

beginner

Write what you want in plain sentences, see how they were read, sign the promises, and get the change running in your app

2026-10-04
Thinkube Tandem 30 min

Build the improvements Tandem’s reviewers suggest

beginner

Keep the findings a report lists, put them in the box as sentences, and build them without touching what is already built

2026-10-04