MessyData – turn messy data into clean tables/CSV
Useful for quick cleanup, but JinaAI and LLMs already handle this natively.

Agent-guided compilation handles merged cells and multi-level headers LLMs choke on.
Data engineers, analysts working with real-world spreadsheet data
Flatfile · Row Zero · Jina AI Reader
The core issue: most real-world spreadsheets aren't relational tables. Merged cells, multi-level headers, multiple tables per sheet, totals mixed in with data. You can't just dump them to CSV and call it done. LLMs handle the easy cases but fall apart on complex workbooks at scale.
Our approach uses an agent-guided compilation pipeline that produces SQL-ready relational tables with full cell-level provenance. This demo visualizes what we do: https://storage.googleapis.com/deeptable-public/deeptable_an...
We have a handful of early customers but honestly don't know yet whether this is a real market or a niche problem. We're posting this to hear from people who've dealt with arbitrary spreadsheet ingestion. Whether you solved it, gave up, or are still living with the pain.
If you want to try it on your own files, email me (see my profile for my email) and I'll give you API access.
Useful for quick cleanup, but JinaAI and LLMs already handle this natively.
Automated CSV cleaning with AI insights, but OpenRefine handles larger datasets for free.
CSV cleaner with deterministic transformations, but remove.bg pattern—solves friction, not novel.
Bank-specific parsers beat generic OCR for QuickBooks imports.
Glide and Softr already turn spreadsheets into apps with more maturity.
Catches silent data failures (schema drift, type mismatches) before pipelines break.