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InsightOS
GitHub
Explainable analytics engine

Power BI tells you what happened.InsightOS tells you why it happened and what to do next.

Point it at a dataset and it profiles the schema, infers the business domain, derives the KPIs that matter, tests every candidate driver for statistical significance, and writes the executive brief. No dashboard authoring, no configuration, no backend.

View source

Your data never leaves your device. All analysis runs locally in your browser.

How InsightOS analyses a dataset

The pipeline
  1. 01

    Upload

    CSV, Excel, JSON or Parquet parsed in your browser with DuckDB-WASM.

  2. 02

    Automatic KPI discovery

    The domain is inferred, then the KPIs that matter for it are derived.

  3. 03

    Root cause analysis

    Every driver is tested for significance and ranked by contribution.

  4. 04

    Executive recommendations

    Deterministic rules produce owned, auditable actions.

  5. 05

    Report

    A written executive brief you could send without editing.

Dataset playground

Bring nothing. Every dataset below is already analysed.

Each one carries a real analytical story: a planted regression that the engine has to find on its own. Pick a domain to open the workspace.

What makes it different

Nothing is a black box

Every recommendation exposes the evidence rows, the statistical test used, the rules that fired, the alternatives that were rejected and a timestamped audit trail.

Statistics, not vibes

Drivers are ranked by contribution and screened with Poisson, chi-square, Mann-Whitney and Mann-Kendall tests, with Benjamini-Hochberg correction across the candidate set.

Governed by design

Datasets are scored for quality, freshness and trust, then assigned a decision-readiness level. Poor data caps the confidence of every recommendation derived from it.

Private by default

Sensitive columns are detected by name and by value, masked automatically, and excluded from drill-down until you explicitly allow it.

Real SQL, in the browser

DuckDB-WASM registers your file as a table. The analytics run as SQL you can read, and the SQL console lets you query the same tables directly.

A framework, not an app

The analytics core is a reusable Python package with per-domain plugins that supply KPIs, dimensions, root-cause rules and forecast settings.