Describe the result.
Datapia builds the workflow.
Datapia turns plain-language instructions into reliable data pipelines. Load a file, describe the result you need, and generate validated transformations, reports, and charts. Run the same workflow on every future dataset and get consistent results — always under your control.
See it in one minute
A real bank export: clean it, categorize every transaction, build a spending chart. Next month — drop in the new file and the whole pipeline reruns, with no AI involved and no credits spent.
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How it works
A pipeline is a single line from raw file to finished artifact. Every step is a station you can inspect.
Pick any CSV, Excel, or JSON file. It is read right on your computer — nothing is uploaded. Datapia shows exactly what it detected: columns, types, and patterns.
Tell Datapia what you want in plain language. No formulas or coding. The AI translates your intent into a validated transformation workflow.
Datapia builds a repeatable pipeline and runs it on your computer. You get clean datasets, reports, and charts — ready to use or export.
Next month, new file. Same pipeline. One click rerun. Same logic, consistent results every time — without re-explaining anything.
Private by design
Your file never leaves your computer. To write each step’s code, the AI sees column names, types, stats and a few example values — never your file.
Say it plainly — tune it if you want
Describe the transformation in plain language and get consistent, validated results every time. Pro users can inspect and refine the generated code directly.
Also drop rows where amount_usd is negative.
def transform(df):
df = df.drop_duplicates(subset=["order_id"])
df = df.dropna(subset=["customer", "amount_usd"])
return df[df["amount_usd"] >= 0]
Start your first pipeline in minutes
Early access is free: ten AI pipelines and the full describe-to-artifact workflow. Nothing to install.