FantasyLab-ai/aurora

### Glass-box quantitative intelligence. Local. Open. Cited.
Aurora is the **verification cortex** for serious quantitative work — for humans analyzing hard data, and for AI systems that can't afford to hallucinate.
> **Cloud LLMs guess. Aurora computes.**
**⬇️ Download the desktop app** · Run from source · Aurora Sentinel demos · See it in action · Aurora Copilot · Aurora Cortex (MCP + SDK) · Roadmap · FantasyLab.ai
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⬇️ Download the desktop app
**The easiest way to run Aurora — no Python, no terminal, no setup.** Download
the installer for your OS, double-click, and Aurora opens as a native app with
the analysis backend bundled inside it.
→ **Download the latest release**
Pick the file that matches your OS (filenames carry the version, e.g. 0.2.0):
| OS | File to download | Install |
|---|---|---|
| **Windows 10/11** | Aurora_x.x.x_x64-setup.exe **(recommended)** | Run the setup wizard. |
| Windows 10/11 | Aurora_x.x.x_x64_en-US.msi | Alternative MSI installer (same app). |
| **macOS** (Apple Silicon · M1/M2/M3/M4) | Aurora_x.x.x_aarch64.dmg | Open the .dmg, drag Aurora to Applications. |
| **Linux** (Debian / Ubuntu / Mint) | Aurora_x.x.x_amd64.deb | sudo apt install ./Aurora_x.x.x_amd64.deb |
| **Linux** (Fedora / RHEL / openSUSE) | Aurora-x.x.x-1.x86_64.rpm | sudo dnf install ./Aurora-x.x.x-1.x86_64.rpm |
> Aurora_aarch64.app.tar.gz is an auto-updater artifact, **not** a download —
> use the .dmg on macOS. There is currently no Intel-Mac (x86_64) or Linux
> AppImage build; Intel-Mac users can run from source.
On first launch Aurora bootstraps a small knowledge-bank seed, then runs **fully
offline** — no API keys, no cloud, no telemetry. Drop a CSV on the window and
watch it analyze. Aurora is **local-first: your data never leaves your machine**
unless you explicitly share a single finding — see PRIVACY.md.
> **Heads up on the "Unknown Publisher" warning.** Current releases are not yet
> code-signed, so Windows SmartScreen may show *"Windows protected your PC"* and
> macOS Gatekeeper may say *"unidentified developer."* This is expected for a
> young open-source project. On Windows: **More info → Run anyway**. On macOS:
> **right-click the app → Open**. Code-signing is on the roadmap.
Desktop app — tips & known quirks
A few things that are **expected behavior**, not bugs:
- **First launch shows a welcome screen, not a run.** That's intentional — a
fresh start is clean. Drop a CSV (or click a demo card) to begin; your past
runs are always available under **Data → Bundles**.
- **Give the backend a few seconds on first launch.** Aurora starts a local
analysis server (127.0.0.1:8001) the first time you open it; the status dot
reads "connecting…" for ~5–10 s before it goes live. If it lingers, the app
is still warming up — it is not frozen.
- **Big datasets take longer, and results land all at once.** A large file can
spend a while in *"analyzing…"*. When it finishes you'll see *"analysis
complete"* and the views populate. If the Overview looks momentarily empty
right after completion, give it a few seconds or click another tab and back —
the assembled state is still being fetched, and it will fill in.
- **Re-running the same file is instant.** Identical data + settings reuse a
cached analysis; the banner reads *"instant · cached."* That's a speed win,
not a skipped run.
- **Knowledge Bank starts small on a fresh install.** The bundled app ships with
a seed bank that grows over time; the large multi-thousand-entry bank you may
see in screenshots is built up on a machine that's been ingesting data for a
while. Citations still work against whatever is local.
Want to build it yourself or run from source? Keep reading.
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⚡ Quickstart (60 seconds)
Open . Click **▶ Try a demo** for an instant smoke test, or drop your own CSV / Parquet / JSON / XLSX.
> First run will download a small knowledge-bank seed (~50 MB). After that, Aurora runs **fully offline** — no API keys, no cloud, no telemetry.
**Optional extras** (only if you need them):
For the optional Vite + TypeScript frontend build (developers only), see § Optional frontend build.
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🖥️ The desktop app
A native, installable app — frameless window, sidebar navigation,
drag-and-drop any file onto it. Built with Tauri 2, with Aurora's **full
analysis backend bundled inside the installer**, so it runs with zero
setup: no Python, no venv, no terminal.
> **Most people should just download it.**
> The rest of this section is for developers who want to build it from
> source or hack on the UI.