FluxDI — Declare your data warehouse. We'll build the pipelines.

The problem

Enterprise data teams have three bad options for building warehouse pipelines.

Each option leaves the hardest parts — accurate history tracking, consistent change-tracking policies, and moving data between engines — as recurring engineering work that drifts over time.

Option 1

Hand-write SQL & Python

Fast to start. Impossible to keep consistent across hundreds of tables. History tracking is bug-prone, and accurate point-in-time reporting is rarely achieved.

Option 2

Buy a heavyweight ETL suite

Expensive, visual-editor heavy — and the hard parts (full history tracking, change reconciliation, cross-engine data movement) still get hand-coded inside the boxes.

Option 3

Adopt dbt + glue code

Solves the transformation layer beautifully. Doesn't solve source-to-warehouse history, cross-engine data movement, change-tracking enforcement, or schema-as-config.

FluxDI fixes the metadata-to-pipeline gap.

Four pillars

A platform, not a methodology. The shape of every pipeline is decided by your metadata.

A few simple facts about each table — its purpose, its keys, what its columns mean — are enough for FluxDI to generate the entire pipeline. Change the facts, and the pipeline updates itself.

PILLAR 01

One Source of Truth

Describe your tables, columns, keys, and what they mean — once, in one place.

A single catalog the whole team can rely on
Master data, lookups, and environments organized for you
Define once, reuse everywhere

PILLAR 02

Prescriptive Architecture

A guided path from raw source data to business-ready marts — with rules enforced at every stage.

Best-practice layering, applied automatically
Change-tracking policies derived for you
Inconsistencies caught before they ship

PILLAR 03

Pipelines, Generated

The right history-tracking pipeline picked automatically for every table you load.

No hand-written history logic
No fragile timeline reconciliation
Tuned to whichever warehouse engine you use

PILLAR 04

Studio for Operators

Define, preview, run, and monitor — all in one modern web interface.

See exactly what will run, before it runs
Live progress as pipelines execute
Color-coded environments to prevent costly mistakes

How it works

From raw source to business-ready data, in four guided stages.

A clear, repeatable path every table follows — with the right history-tracking strategy chosen automatically along the way.

The journey of every table

Connect
Read from your source systems

Land
Capture a fresh copy, audit-stamped

Integrate
Reconcile per-source with history

Warehouse
Facts & dimensions, point-in-time accurate

Publish
Business-ready marts for analysts

Full-history pipeline

Auto-selected

For tables where "what was true at any point in time" matters — pricing, contracts, employee records, anything you need to report on as-of a past date.

Tracks both when something was true in the real world and when FluxDI learned about it
Lets you reconstruct any historical view, exactly as it was
Handles late-arriving and back-dated changes correctly, without re-runs
Audit-ready by default

Change-log pipeline

Auto-selected

For tables where you only need "what we knew, and when we knew it" — operational data where the source system already owns the timeline.

Lightweight, with a complete arrival-time audit trail
Lower storage and compute footprint
Replays history of what FluxDI received from each source
Ideal for raw operational feeds & CDC streams

Move data between engines

Move tens of millions of rows between warehouses — no staging files, no extra infrastructure.

FluxDI streams data directly between supported engines, with automatic type translation so columns land in their correct shape on the target. Built for production-scale moves — migrations, replications, and ongoing syncs — without standing up an extra processing tier.

High-throughput streaming Auto type translation No extra infrastructure

PostgreSQL

source

FluxDI

in-flight

Teradata

target

FluxDI Studio

The single workspace for everyone who touches your warehouse.

A modern web interface where data engineers define the work, data leaders monitor it in real time, and everyone shares the same view of what's running, what's passing, and what needs attention.

Live monitoring

One dashboard for KPIs, table health, and the runs currently in flight.

Preview before you run

See exactly what FluxDI will do — every step, every table — before anything executes.

Visual table editor

Define columns, keys, and meaning in a spreadsheet-style grid. The platform handles the rest.

Live progress & alerts

Watch each table load in real time. See errors the moment they happen.

Safer environments

Color-coded Production, UAT, and Dev — so nobody ever runs the wrong thing in the wrong place.

Bring your existing catalog

Upload a spreadsheet of your existing tables and FluxDI imports them in seconds.

fluxdi.com

FluxDI Studio dashboard with pipeline KPIs, run history, and recent activity

About

Built by data engineers who got tired of solving the same problem on every project.

FluxDI is currently in early access — being validated alongside a select group of partner organizations before general availability.

The team behind FluxDI

This section is reserved for the founder story, team bios, and origin of the platform — what problem you personally hit that motivated building FluxDI, and where it's headed.

Drop in your name, role, the origin story, and any team or company structure you want to surface. Everything else on this page is ready to ship without it.

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Get in touch

Want to see what FluxDI generates for your warehouse?

Tell us about your use case. We'll send back a short demo that takes one of your tables and shows you what FluxDI would build for it — end to end.

What to expect

We respond within two business days. The demo runs against your schema, in a sandbox we provision — no production credentials required.

A demo against your dataWe point FluxDI at one of your tables (or a sanitized sample) and show you what it generates — end to end, in your warehouse.
A walkthrough of the Studio20-minute screen-share covering how teams define, preview, run, and monitor pipelines in one place.
An honest fit assessmentIf FluxDI isn't right for your warehouse, your scale, or your history needs — we'll tell you on the call.