Lab grids and billing tables, read as data — not images.

Extract data from lab reports, med lists, and billing grids as structured rows — vision AI sees the grid, not just the glyphs, and parses complex medical tables into data you can query rather than view. Every lab value and billing line becomes queryable, and each extracted number stays tied to the table it came from.

Vision AI sees the grid, not just the glyphs.

Plain OCR flattens a table into word soup: headers drift away from their values, merged cells collapse, units vanish. A vision model detects the table itself — header rows, row spans, units columns — and reads each cell in its place.

Every lab value becomes something you can query.

Once a grid is rows, questions get answers. Pull every result for one analyte across the whole file, sort it by date, and see the trend instead of hunting page by page. Extracted rows feed Search, Chat, and Smart Lists automatically.

Med lists and billing grids, read the same way.

Medication tables become drug, dose, and frequency rows; billing grids become line items you can total and trace. The same table engine powers billing verification and cost roll-ups downstream, so the data only has to be read once.

A number without its table is just a claim.

Every extracted row cites the table and page it came from: click a value and land on the original grid. Cells the model can’t read cleanly are flagged, not filled. That discipline is what makes the data audit-grade — it survives cross-examination because it traces to source.

Lab reports, med lists, and billing statements go in as they are — scans, faxes, and photographed pages included.

A vision model finds every grid, reads its structure, and extracts each cell into a structured row with its citation.

Search one analyte across the file, filter medication rows, or send billing lines downstream to roll-ups and audits.