Eigenius runs on your laptop. The walkthrough is a notebook; each cell commits a typed artifact to the chain, and the kernel type-checks the composition as it goes. By the end you have a machine-checkable audit trail from six raw plate-reader readings to a published-style designation.
Every cell commits a typed chain artifact. The right pane surfaces the audit trail the kernel just type-checked — not a rendered summary, the actual chain. Below is the drug-screening walkthrough partway through.
The end-to-end demo runs entirely in Docker — no Rust or Deno on the host required. If you'd rather build from source, follow Platform §2 — Installation instead.
git clone https://github.com/eigenius/eigenius
cd eigenius
docker compose up -dRequires Docker Desktop or Docker Engine + Compose v2. The first run pulls images and seeds the layer chain — allow a couple of minutes.
http://localhost:8080/notebooks/No login. Everything runs on your laptop. The orchestrator serves the React notebook and proxies EigenQL/ESL into the kernel over gRPC.
Open examples/stats-and-reasoning.json
and run cells top to bottom. About five minutes
end-to-end. Watch the AutoOnLoad cascades fire as the
statistics institution emits its verdict and the
reasoning institution composes the certificate.
Read the walkthrough first Platform §14 — Notebook reference
By the time the last cell runs, you have committed:
A reviewer (or another AI agent, or a regulator) can now walk back from the conclusion to the raw data in finite steps, re-execute any deterministic step, and refute any premise without disputing the rest.
The framework's vocabulary in narrative form.
Worked end-to-end walkthroughs.
Surface languages, queries, and the platform.
Project tracking lives on GitHub. Use Discussions for open-ended questions and design conversations; file an Issue with the smallest reproduction you can manage when something is broken. For private deployments and commercial questions, see the contact note in the repo README.