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Read Jicate ExplainedShip production data pipelines that come with security, data quality, and governed teamwork built in from day one.
Coding skills not required.
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A rethought architecture separates schema work from data work, so you can build and preview pipelines interactively — at full production scale — without the usual wait.
A clean point-and-click canvas lets anyone on the team — technical or not — assemble complex pipelines and shape data, no engineering background required.
This isn't just for small datasets. Handle batch, micro-batch, and streaming workloads across structured, unstructured, IoT, and geospatial data alike.
No-code, low-code, and pro-code teams work side by side. Export to code and lean on open standards so nothing is ever locked in.
Stop fighting code, libraries, builds, and repository sprawl — and put your time into the work that actually moves the needle.
Begin by picking the datasets you want to work with directly inside Foundry.
Pull data in from virtually any source system — structured, unstructured, IoT, or geospatial — with minimal setup.
Need a quick one-off? Drag and drop raw files straight into Foundry.

Plug into whichever execution engine fits the job — Spark, Flink, and others are all supported.
Branch and version freely to experiment safely and roll out changes with confidence.
Lift logic out of one pipeline and reuse it in another, saving the time and cost of rebuilding from scratch.
Strong typing surfaces errors as you build rather than at run time, heading off breaks that are expensive to repair.
Describe the pipeline and the outputs you want; builds, syncs, and orchestration are handled for you in the background.
When the expected output target isn't satisfied, deployment is blocked to protect everything downstream.
Granular security checks and Git-style change control come standard — without slowing you down.
Export to code at any time, on an architecture built from the ground up to stay runtime-agnostic and lock-in free.