AetherData: enterprise data fabric.
A modern data platform that connects scattered sources — APIs, SaaS apps and databases — and turns them into structured, analytics-ready data through no-code and SQL-based pipelines, so teams can query a governed warehouse without waiting on engineering.
The challenge.
- Enterprise data sat in silos across CRMs, ERPs, billing, product analytics and spreadsheets, so every executive question kicked off a three-week data-engineering ticket.
- Existing ETL tooling demanded deep engineering investment for every new source, and schemas drifted silently between pipelines and dashboards.
- The founding team needed to connect hundreds of systems, keep lineage auditable, and expose a governed warehouse that analysts could query without bothering engineering.
Our approach.
- Built a modern data platform that integrates, transforms and analyses data from many sources in one place.
- Wired a connector-based ingestion layer for APIs, SaaS apps and databases, automatically turning raw feeds into structured, query-ready data.
- Shipped a React front end where analysts compose pipelines with a no-code builder or raw SQL, on a Django and Django REST Framework backend over PostgreSQL.
- Added a warehouse abstraction layer so business teams work against clean, governed data instead of raw source systems.
The outcome.
- Business teams self-serve integrations and dashboards that previously needed engineering.
- New data sources move from raw feed to query-ready in a fraction of the previous effort.
- A governed, structured warehouse analysts can query directly for decision-making.
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Where AI fits in manufacturing & industrial.
Assistants that answer engineers' questions from manuals and maintenance history, visual quality checks, and procurement workflows that draft, compare and route supplier documents.
Explore AI developmentQuestions about this build.
Still wondering something? Ask an engineer
A React front end with a Django and Django REST Framework backend over PostgreSQL, wrapping a connector-based ingestion and transformation layer.
It connects scattered data from APIs, SaaS apps and databases, automatically turns it into structured data, and exposes it through no-code and SQL-based pipelines as an analytics-ready warehouse.
Analysts and business teams — the no-code builder plus SQL means new sources and dashboards no longer require engineering involvement for every change.
Let's build from here.
Thirty minutes with an engineer who builds. No sales, no drip campaign. If we're the wrong fit we'll tell you and point you somewhere better.