The AI comes to your data —
not the other way around
Cloud AI works by sending your data out to someone else's servers. Coot flips it: modern AI models run on hardware you own, right where your data already lives. Here's exactly how that works.
Two ways to run AI — only one keeps your data
The difference isn't the model. It's where the model runs. Follow the same request through both.
Cloud AI
- 1You send your prompt and files to a provider
- 2They run the model on their servers
- 3Your data is stored — and can be trained on
- 4The answer comes back; the copy stays with them
Your data leaves your control
With Coot
- 1The model is already running on your hardware
- 2Coot indexes your data locally — nothing is uploaded
- 3The model reasons over your own material in place
- 4The answer, and your data, never leave your control
Your data never leaves your control
From download to private AI, in four steps
No stack to assemble, no server to run. Each piece is already built in — you're just pointing it at your world.
- Step 1
Install one app
The runtimes, agent engine, connectors, and interface all ship inside a single download — already wired together. There's no stack to assemble and no server to stand up.
- Step 2
Point it at your data
Add the folders, drives, and inboxes you want your AI to know. Coot indexes them locally on your hardware — building a private, searchable picture of your material without uploading a byte.
- Step 3
Pick your models
The built-in Model Hub recommends local models that will run well on your hardware and handles the download. Swap them any time — they all run on your machine.
- Step 4
Put it to work
Chat, hand off multi-step jobs to agents, or build workflows that run on a schedule. Every request is answered by a model running locally, over your own indexed data.
Everything a private AI stack needs — in one install
Running local AI yourself usually means bolting these layers together and keeping each one alive. Coot ships them as one system, connected and configured, all on hardware you own.
Local model runtimes
Optimized engines run models directly on your CPU and GPU — bundled, so there's no runtime to install or quantization to fine-tune by hand.
Model Hub
Browse, download, and switch between local models for chat, reasoning, code, and embeddings — each matched to the hardware you have.
Local knowledge index
Your documents and drives are embedded and indexed on-device, so models can search and answer over your own material — retrieval, entirely in place.
Agent engine
Coot's engine plans multi-step work, calls the right models and tools, and sees a job through end to end — not just a single reply.
Connectors
Gmail, Outlook, Slack, Calendar, Google Drive, and Dropbox plug in — Coot handles the OAuth and token refresh so your AI works with the systems you already run on.
Workflows & scheduler
Build processes in a visual studio and run them on a schedule — the automation, retries, and timing are handled inside the app, with no cron to babysit.
Memory
Context carries across sessions, so your AI gets more useful over time — held privately on your own hardware.
One interface
A single, polished app already wired to every layer above — so all of it is usable the moment you open it.
Eight layers → one download. No terminal, no config, no glue code.
Every request stays inside your walls
From the data you add to the answer you get back, the whole loop runs on hardware you control.
Your data
Documents, drives, and inboxes you add
Indexed locally
Embedded on-device — nothing uploaded
Answered on your hardware
A local model reasons and replies
No uploads. No training on your data. No cloud middleman.
Watch the pieces work as a team
The layers aren't separate apps you stitch together — they're one system. Here's a single job, handled end to end: turning a messy inbox into clean books.
The connector supplies the email, a local model reads it, your rules shape the result, and memory keeps the context — no data leaves, and no step is a different service.
- 01
Reads your inbox
A connected inbox brings in invoices and receipts as they arrive.
- 02
Extracts transactions
A local model pulls out amounts, dates, and vendors from each message.
- 03
Applies your rules
Your categorization rules sort every transaction the way you would.
- 04
Builds clean reports
The results become reports you can actually use — all on your hardware.
The same model, shared across a team
Coot runs on your machine as a private workspace of one. Install it across your team's systems and those workspaces link into a shared, permissioned space — a company folder everyone works from, roles and access per member, and authentication handled. It scales from a single person to an organization, and your data still never touches a third party.
- Shared company folder
- Member roles & access
- Permissions & auth handled
- No third-party data sharing
How it works, in detail
Where do the AI models actually run?
On your own hardware. Coot bundles the runtimes and runs models directly on your CPU and GPU. There's no inference server to host and no cloud endpoint in the loop — the model is already running locally when you open the app.
How does Coot answer over my own documents?
When you point Coot at a folder, drive, or inbox, it embeds and indexes that material on-device, building a private searchable index. When you ask a question, a local model retrieves the relevant pieces and reasons over them in place. Your files are never uploaded, and the index stays on hardware you control.
Does anything leave my machine?
Your data doesn't. Models, your indexed files, memory, and conversations all stay on your hardware. The only traffic that leaves is what you explicitly connect — for example, reaching your own Gmail or Slack account through its official API — and even then the reasoning happens locally, and nothing is sent to a model provider.
Where do the models come from, and do I need internet for them?
You download models once from the built-in Model Hub, which recommends ones that fit your hardware. After that they run locally, so day-to-day use of local models works without an internet connection. You only need a connection to download new models or to reach connected online tools.
How do agents and workflows work?
An agent takes a goal, plans the steps, and calls the models and connected tools needed to finish it — reading data, applying your rules, and producing a result. Workflows let you lay those steps out in a visual studio and run them on a schedule, with timing and retries handled inside the app.
How does this work for a whole team?
Install Coot across your team's systems and the individual workspaces join into a shared, permissioned space — with a shared company folder, member roles and access, and authentication handled. It scales from one person to an organization without your data ever going to a third party.
Do I need a technical team to set this up?
No. Coot handles installation, model selection, indexing, and connectors for you. If you can install an app and point it at a folder, you can run private AI over your own data — and grow it as you go.
See it work over your own data
Download Coot free and put private AI to work in minutes — on infrastructure you own. No account required.