Most CSV files are internally inconsistent — the same value appears in five different ways, dates use three different formats, and column names don't match anything. Asphorem maps, normalises, and standardises all of it.
Your file rows are never uploaded. AI matching uses unique column values only.
A dirty CSV isn't broken — it's inconsistent. The same information is expressed in a dozen different ways, and every downstream tool rejects it.
Upload your file, define what clean looks like, and download the result. Your file rows never leave your machine — only unique picklist values are shared with the AI for matching.
Drop any CSV. Asphorem reads the headers and gives you a preview of the raw data — including a breakdown of unique values per column, so you can see the inconsistencies at a glance.
Tell Asphorem what each column should be called and what type it holds — Text, Number, Date, or Picklist. Set the allowed values for picklist columns. Save this schema as a reusable property set.
For each picklist column, the AI maps every unique cell value to the correct canonical value — catching typos, language variants, abbreviations, and capitalisation differences. Dates are unified to ISO format automatically.
Every mapping is shown before export. Fix anything the AI got wrong with a single click. Your corrections are remembered for future runs of the same file format.
Data standardisation isn't just an import problem. Inconsistent values cause issues anywhere data is read, merged, or reported on.
You export data from two CRMs, a spreadsheet, and a data provider. Each has different conventions. Before you can merge them, every column and value needs to match a common standard — or you end up with duplicates and gaps.
You collected or processed data on behalf of a client, and they need it in a specific format. Clean the file to match their column names and allowed values before you send it — not after they email you with corrections.
Dashboards and BI tools break when the same category appears under twenty different spellings. Standardise your picklist columns first so filters, groupings, and aggregations actually reflect reality.
Every CRM validates field values on import. If your data doesn't match the expected picklist, the row either fails or imports blank. Clean the file first so the import works without errors or manual cleanup after.
Your CSV file is loaded and processed locally — no rows are ever transmitted to our servers or stored anywhere. The only things we store are your account details and the mapping configurations you create.
When you use the AI matching feature, the unique values from the columns you choose to map are sent to the AI for analysis. These are deduplicated picklist values (e.g. the distinct values found in a "Status" column) — not full rows, not names, not IDs, not any other field you haven't explicitly chosen to map.
If your files contain sensitive picklist values you'd prefer not to share, you can always map those columns manually instead.
Free plan included. No credit card required.
Start for free →