Ravel
Local-first personal AI agent

An AI agent, quietly running on your machine.

Ravel remembers everything that matters, connects to 118+ tools, and acts on your behalf — running locally, on an open agent network.

curlcurl -fsSL ravel.sh | sh
Ravel — Overviewlocal · private
agentactive
runtimev0.3.8
memory412k nodes
modellocal + routed
memory tree1.2 GB · local
agent activity
Indexed 12 messages from Gmailnow
Compressed memory tree · −78% tokens2m
Routed task → fast model4m
Auto-fetch cycle complete11m
Connected Linear workspace20m
connections
Gmailsynced
GitHubsynced
Notionsyncing
Calendarsynced
Linearidle
The workspace

An AI workspace you actually run

This is the real Ravel interface — try it right here. Switch views, filter tasks, search memory, press ⌘K.

Agent Workspaceravel://workspace
localOpen full ↗
2 running6 of 6
reasoning timeline · 64%
  1. ·read 38 messages from memory tree
  2. ·cross-referenced 12 calendar events
  3. drafting summary…
interactive demo · runs entirely in your browserOpen full workspace ↗
Live · gitlawb network

Watch Ravel learn in real time

New repositories appear on the open network — Ravel ingests each one, maps it, and adds it to memory. Click any repo to open it.

streaming from gitlawb0 repos on network · 0 learned this session
connecting to gitlawb network…
Architecture

How Ravel turns your tools into memory

Four stages, running locally — from raw data to autonomous action.

01
Ingest

Connects and reads

118+ OAuth integrations stream your data in. Auto-fetch refreshes every 20 minutes so context is never stale.

02
Compress

Builds the memory tree

A local LLM compresses everything into a deterministic memory tree in SQLite — TokenJuice cuts token use up to 80%.

03
Route

Picks the right model

Each task is routed to a reasoning, fast, or vision model — the cheapest one that can do the job well.

04
Act

Executes on your behalf

Native tools — web, scraper, coder, voice — let Ravel finish work in the background, then report back.

How it works

From install to autonomous agent

Three steps. No configuration, no ramp-up period.

01

Connect your tools

One-click OAuth into 118+ apps — email, calendar, notes, code, and chat.

02

Build a memory tree

Ravel compresses everything into a local, deterministic memory you fully own.

03

Let the agent act

Ravel works in the background, routes tasks to the right model, and gets things done.

Capabilities

Everything a personal agent should be

Memory, integrations, and a full toolbelt — running locally.

1B-token memory

A persistent memory tree stored locally on your machine — no ramp-up, ever.

118+ integrations

One-click OAuth connections to the tools you already use every day.

TokenJuice compression

Up to 80% fewer tokens via smart HTML-to-markdown conversion and summarization.

Native toolbelt

Web search, scraper, a full coder toolset, and voice — built in.

Private by default

A local LLM handles low-level work so your data stays off the cloud.

Smart model routing

Reasoning, fast, or vision — the right model for each task, one runtime.

Use cases

One agent, every kind of work

Ravel adapts to how you work — here is what it does for different people.

Developers

Ravel reads your repos, tracks PRs, and drafts code with full context of your codebase — no copy-pasting.

$ ravel run 'review PR #418 and suggest fixes'

Founders

Inbox, calendar, docs, and Stripe in one memory. Ask for a weekly summary and Ravel just knows.

$ ravel run 'summarize this week across all tools'

Researchers

Feed Ravel papers and notes; it builds a searchable knowledge tree and surfaces connections you missed.

$ ravel run 'find links between these 40 sources'
0B
tokens of memory
0+
integrations
0%
fewer tokens
0min
auto-fetch cycle
Live · gitlawb network

Always indexing, always learning

Ravel watches the open network and folds every new repository into its memory — here is the stream, live.

indexed
mdpreviewmy-first-repominebean-contractsmy-projectagent-runtimememory-treemdpreviewmy-first-repominebean-contractsmy-projectagent-runtimememory-treemdpreviewmy-first-repominebean-contractsmy-projectagent-runtimememory-treemdpreviewmy-first-repominebean-contractsmy-projectagent-runtimememory-tree
Why Ravel

Built different on purpose

Most AI assistants run in someone else's cloud. Ravel does not.

capabilityRavelOthers
Runs locally
Your data stays on-device
Open-source
Persistent 1B-token memory
118+ native integrationsSome
No subscription
Free to use

Ravel is free — and stays yours

No subscription, no paywall, no per-seat pricing. Ravel is open-source and local-first, so every feature runs on your own machine at no cost.

  • All 118+ integrations included
  • Full 1B-token memory tree
  • Smart model routing and native tools
  • Open-source — yours to inspect and extend
FAQ

Questions, answered

Yes. Ravel is local-first — your memory tree lives in SQLite on your machine. A local LLM handles low-level work, so your data never has to leave your device.

Roadmap

Where Ravel is headed

Phase 1

Integrations

118+ one-click OAuth connections and the auto-fetch engine.

Phase 2

Agent toolbelt

Native web, scraper, coder, and voice tools shipping now.

Phase 3

Desktop presence

The mascot joins calls, lip-syncs, and reacts in real time.

Get started

Install Ravel in one line

Free, open-source, and local-first. One command and the agent is yours.

$curl -fsSL ravel.sh | sh
macOSWindowsLinux