Aurora

Aurora is glass-box quantitative intelligence — local, open, and cited. It's the verification layer for serious quantitative work: for humans analyzing hard data, and for AI systems that can't afford to hallucinate.

Every AI today invents numbers on quantitative claims — bigger models and RAG don't fix it. Aurora is the structurally different fix: it computes and verifies instead of predicting. Drop in a dataset (CSV, Parquet, JSON, XLSX) and it runs 24+ research-grade methods — Isolation Forest, robust z-score, Granger causality, HMM regimes, SINDy physics discovery, Gaussian processes, persistent homology, and more. Every finding is a structured object with a method, severity, threshold, and a citation linking to the exact knowledge-bank entry behind it — real sources like Newton, Granger, NIST, and NOAA. No invented numbers, no invented papers. A live "0 fabricated" chip is the contractual signal that every claim traces to a computation.

Cloud LLMs guess. Aurora computes.

Aurora has two faces sharing one engine. Copilot is the local studio for analysts, quants, scientists, and engineers — six analytical lenses, a spacetime system graph, and phase-space projection for exploring findings visually.