Analysis

Data Cleanup

Normalises messy exports and documents every transformation.

About

Deduplicates, normalises fields and flags rows that need a human decision. The transformation log stays with the file so results remain reproducible.

How to use

Upload the export, state the target schema and ask for the transformation log alongside the clean file.

Step by step

  1. 01

    Define the schema

    Say exactly which fields and formats you expect.

  2. 02

    Run the cleanup

    Deduplicate, normalise and flag ambiguous rows.

  3. 03

    Keep the log

    Store the transformation log next to the output file.

What you get

Clean dataset
Flagged rows
Transformation log
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Client voices

What teams say after the week

Short feedback from hackathons with engineering, marketing, operations and leadership teams.

Our engineers built a code-review assistant in two days that the whole team still uses. No training ever did that.
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The whole agency was building. Marketers with zero coding background shipped content pipelines that saved real hours.
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Procurement workflows that used to sit on a roadmap were prototyped and demoed inside the same week.
Head of operationsOnventis
Our leadership cohort left with five working agents and a completely different sense of what AI can do for us.
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