Legacy file modernization

Convert fixed-width files to CSV, typed and clean.

The extract lands every night, the layout lives in a PDF from 2009, and the parsing script that understood both left with its author. Describe the column positions, or upload the layout document and let the AI extract the field definitions into a data dictionary. The generated scripts slice and type every column, and the sealed run handles the nightly file identically every time.

Free plan available. No card required.

No data sent to a model at run-time · transparent, versioned scripts
Fixed-width to CSV
Input · positional extract (synthetic)
0001JANE DOE            20260131000125000USD
0002ACME LOGISTICS LLC  20260131001480050USD
0003RIVERSIDE CLINIC    20260201000093200USD
▾ AI-written transformation, reviewed and versioned
Output · ledger.csv
acct,name,date,amount,currency
0001,Jane Doe,2026-01-31,1250.00,USD
0002,Acme Logistics LLC,2026-01-31,14800.50,USD
0003,Riverside Clinic,2026-02-01,932.00,USD
Runs with no AI, your data stays out of the model

How it works

From a messy file to a tested pipeline, in minutes.

1

Describe it and bring your spec

Plain English, plus a sample, a spec, or a data dictionary. Cannot share data at all? Build from the spec alone.

2

AI writes transparent scripts

You get reviewable, versioned Python, never a black box. Inspect every line and preview the output on a sample.

3

Run it anywhere, with no AI

Trigger by API, schedule, or click, or pull from SFTP, S3, or Azure Blob. The sealed script does the work; nothing goes to a model.

The AI builds it. A sealed script runs it.

Most AI data tools push records through a language model on every run. We keep the model in the build phase only, so production never sends your data to a model.

Build (one time): AI writes the scripts, from your spec, or a sample you control
Every run after: sealed sandbox, no network, no AI, no data to any model

Full data-flow table and sub-processor list in our Trust Center →

Common questions

Fixed-width to CSV, answered.

Where does the layout come from?

Three options: describe the positions in plain English, upload the layout spec and let the AI extract field definitions, types, and formats into a data dictionary, or provide a sample and describe what each region means.

Can we build this without sharing any real data?

Yes. A data dictionary or layout spec is enough to generate the scripts. The model sees structure, never records, and at run-time nothing is sent to a model regardless.

How do we automate the nightly extract?

Point an SFTP, FTP, S3, or Azure Blob connector at the drop location and schedule the pickup. The sealed script runs on each new file and the output is delivered or ready for download.

Describe it once. Run it forever.

Build the transformation on a sample in minutes, review the scripts line by line, and let the sealed runs handle every file after that.