We got tired ofthe integration tax.
Every data team knows the drill: one tool to move data, another to model it, a third to govern it, a fourth to watch quality. Then two years and an uncomfortable number of zeros spent wiring them together. We thought that was a strange way to run things. So we built Ziggy.
One connected system, not seven stitched together
Ziggy covers the whole life of your data — from the moment you point it at a source to the governed data product someone downstream actually trusts. Underneath all of it sits a single knowledge graph, so everything knows about everything else. Change a column and Ziggy can tell you, instantly, what breaks and who needs to know, the part most platforms cannot do, because their pieces were never meant to share a house.
- Connect and discover — point Ziggy at a source and watch the graph build itself
- Move and model — pipelines, transformations, and a meaning layer that speaks in business terms, not table names
- Trust — data quality, profiling, and availability monitoring that flag trouble before your stakeholders do
- Govern — every change to your data and the code that shapes it, reviewed, approved, and traceable in one place
- Explore — lineage and blast radius on every node, so "what does this affect?" is always one click away
You do not just use Ziggy. You own it.
Your data platform is too important to rent on someone else's terms. So Ziggy ships with its full source code, as standard. Read it, audit it, run it on your own infrastructure, extend it yourself, or have us manage the whole thing — your call, not ours.
- Full source code, delivered as standard — no black boxes, no abstraction you cannot see through
- Run it on your own infrastructure, or let us manage it for you
- Extend it yourself instead of waiting on someone else's roadmap
- No per-seat pricing and no lock-in clause buried on page nine
- Because you hold the code, Ziggy outlives whatever happens to us
Built to keep up with you
Ziggy was designed from the ground up to be operated by AI coding agents — with the skills, processes, and tests baked in. That is how a platform this broad stays coherent, and how it can keep growing at the speed your business does, rather than the speed of a release calendar.
- Engineered for AI-assisted development — skills, conventions, and tests built in from day one
- A consistent shape across every module, so the system stays coherent as it grows
- New capabilities land in days, not quarters
- The same discipline whether we extend it or you do
We like removing seams
We like systems that explain themselves, and we genuinely believe the companies who win the next decade are the ones who own their data foundation rather than assembling it from rented parts and hoping the bill stays flat. If that sounds like the way you would want to work too, we should talk.