Introduction

What Introzen BI is and how the platform fits together.

Introzen BI unifies ingestion, transformation and visualization into one multi-tenant platform. You connect data, describe how it should be shaped, and the platform keeps a materialized dataset that any chart can query in milliseconds.

Try it without an account

You do not have to sign up to evaluate the platform. Open the live demo and the browser is placed inside a seeded workspace - four data sources, four pipelines, fourteen execution runs, a materialised dataset and a populated chart dashboard - with no email, no card and no backend involved. The session is a platform operator, so the platform control centre is open too: fleet health, workspace inventory, the account directory and the cross-workspace execution feed, all seeded. The demo runs entirely in your browser against a built-in API, so it also works when the API is not reachable.

Writes behave like the real thing: creating a source, editing a pipeline, triggering a run, cancelling a run and deleting an execution each change what the next read returns. Reloading rebuilds the fixtures from scratch, so nothing you do in the demo can be left behind, and the Analytics & Charts guide describes the workflow you will be clicking through.

What the platform does

• Ingest files (CSV, JSON) and REST endpoints into a workspace-scoped storage layer.
• Transform data with declarative steps — filter, rename, convert types, sort — instead of hand-written scripts.
• Materialize each run into a columnar Parquet dataset so repeated reads are cheap.
• Visualize that dataset with bar, line, pie, donut and candlestick charts arranged on free-form dashboards.
• Govern everything with workspace isolation, role-based membership and a platform control center for operators.

How it fits together

A request flows from the browser to a Django REST API. Pipeline runs are handed to a background worker pool; progress is streamed back over a WebSocket channel. Finished runs are written as Parquet and served to the analytics layer.

Browser (Next.js app)
      │  HTTPS + HttpOnly session cookie
      ▼
Django REST API ──► Tenant middleware resolves the active workspace
      │
      ├──► PostgreSQL / SQLite  (metadata, membership, settings)
      ├──► Object storage       (uploaded raw files)
      └──► Redis                (Celery broker + Channels layer)
                  │
                  ▼
            Celery worker ──► Transformation engine ──► Parquet dataset
                  │
                  └──► WebSocket ──► live execution log in the browser

The five objects you will work with

Where to go next

If you want to see the platform working end-to-end, start with the Quickstart. If you would rather understand the model first, read Core Concepts.

Last reviewed October 2026.