QuantyDocs

Columns & AI extraction

Columns are where Quanty does its work. A column has a type, and AI columns carry a prompt: when you run the sheet, the model reads each row's documents and writes a value into every cell — with citations, confidence and a full audit trail.

A processed sheet: AI columns filled from five supplier invoices

Column types

When you add a column you pick its type from the Column type grid. The type cannot be changed after creation.

TypeWhat it holds
FileHolds documents or files, one or more per row
Sub-sheetA nested sheet inside a cell, for one to many items
TextAI writes text into each cell: extractions, summaries, answers
NumberAI extracts a numeric value, with formatting options
Single choiceAI picks exactly one of the options you define
Multiple choiceAI picks any number of the options you define
URLAI finds a link, optionally using web search
JSONAI returns structured data matching your JSON schema

Text extraction sub-types

Text columns offer focused extraction modes:

Sub-typeUse it for
Custom PromptAsk anything in your own words, the most flexible type
Entity ExtractionPull out names, companies, places or other entities
SummaryA short summary of each document
ClassificationSort each row into one of your categories
Key-ValueExtract the value for a specific field, like an invoice number
DateFind a date and normalize its format
NumberExtract a formatted number
Document ReferenceReference the document's name and metadata

Number formatting

Number columns have a Data Format section: Currency, Percentage, Date, Decimal or Integer, plus currency symbol and decimal places.

Writing prompts

The Prompt field (up to 1500 characters) tells the model what to extract. Below it, the Model picker lists available models with cost tiers (Premium, Standard, Economy), context window size and a Recommended marker.

Inputs and @-mentions

Columns can read other columns. Type @ in the prompt to mention a sibling column — for example "Compare @Contract Value with @Invoice Total". Mentioned columns appear as chips in the Inputs section, where you can also add them with + add input….

Inputs form a dependency graph: inputs run first, and editing an input column marks this column stale so you know results are out of date.

Source documents

The Source documents selector controls which file columns feed this AI column. By default a column reads the row's documents; narrow it when a sheet has several file columns with different roles.

Knowledge Base

Attach library documents in the Knowledge Base section so the model rates against your house standards. Updating an attached document marks the column stale. See Files & Knowledge Base.

Cite sources

The Cite sources toggle adds page references to every value ("Adds page references · ~20% more tokens"). Citations open in the document viewer with the source highlighted.

Branching and human review

Two settings turn a sheet into a pipeline with routing:

  • Branch — run only when — the column runs only for rows where a chosen Single choice column has one of the selected values. Off-branch cells never compute (0 tokens) and show not on this branch.
  • Route to human review when — for Single choice columns, pick the values that should queue a row into the review panel. This acts as the end-of-pipeline gate; see Reviews & audit trail.

Sub-sheet columns

A Sub-sheet column defines Sub-columns that AI fills per item: each sub-column has a field name and a type — text, number or PY (a Python expression computed per item at 0 tokens). Use it for line items, schedules, or any one-to-many structure inside a row.

AI or Formula

Every value column has a "How this column is filled" choice:

  • AI — "The model reads each document and extracts the value."
  • Formula — "Computes from other columns — deterministic, no tokens spent." See Formulas & Excel mode.

Running the sheet

  • Run AI processes all pending cells. A confirmation explains: "Pending cells will be processed with AI. This uses tokens from your organization's AI budget — you can watch progress and stop at any time."
  • When upstream changes made cells stale, the button offers Update, or "Run AI — also updates N out-of-date cell(s)".
  • Stop halts the run; values already computed are kept.

Cell statuses during and after a run: Completed, Processing, Pending, Failed and Not on this branch. The processing bar shows ready, processing, pending and failed counts, with Retry failed files one click away.

Every run is audited

Each cell keeps an append-only trail of every extraction run — the prompt as it was, the context used, the raw response and cost. You can restore any past value. See Reviews & audit trail.

Compare models (A/B)

From a column's context menu, choose Compare models (A/B)… to run the same prompt with two models side by side and see where they disagree before committing to one.

The pipeline map

The pipeline view renders your sheet as a graph: columns as nodes, dependencies as edges. Node kinds include AI column, Sub-sheet, Sub-sheet column, Documents, Knowledge Base, External data and Formula; edges are labeled documents, value, branch, knowledge base or external data.

Each node shows audit aggregates — Runs, Failed, Tokens, Cost, Avg. confidence and Last run — and the view offers Recompute stale, zoom controls and Export (JSON audit data, light or dark theme, optionally including prompts & formulas, audit stats and value history).

Column management

  • Duplicate column copies configuration (and can copy values).
  • Pin Column left or right, set Width, or Hide from view in Display Settings.
  • Drag to reorder; deleting a column requires confirmation.
  • Column templates save a configured column for reuse across a workbook — pick a template when adding a column instead of configuring from scratch.