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Document AI · Table Extraction

Extract complex tables, line items, and structured relationships with AI.

Artificio understands tables inside business documents, extracts line items and nested data, connects table rows to header key-value fields, detects inconsistencies, and creates structured Table Views ready for validation, transformation, and downstream processing.

Book a demoSee how it works
  • Tables + line items + nested data
  • PDF, image, XLS, TXT
  • SOC 2 Type II
  • ISO 27001
EXTRACT · SUPPLIER_INVOICE.PDFSTRUCTURED
Invoice #
INV-88421
Vendor
Acme Supply Co.
PO
4500012345
Extracted line items
MaterialQtyUnit PriceAmount
MAT-10050$25.00$1,250
MAT-20020$32.00$640
  1. T1Line-item table extracted2 rows · 4 columns · linked to invoice headerREADY
  2. !Discrepancy detectedRow 2 expected amount differs from calculated valueREVIEW
  • Extract line items, multi-column tables, nested tables, and repeated sections
  • Auto-classify different tables on the same page or document
  • Connect header values such as vendor, PO, date, or batch to every extracted row
  • Detect discrepancies while extracting and flag rows that need review
  • Turn paragraphs and unstructured text into structured table records when the data logically belongs in rows and columns
Line itemsExtract structured rows & columns
Nested tablesUnderstand hierarchy and sub-sections
Header-linkedConnect document context to every row
SAP ExecutionValidated & audited

What Artificio extracts

Built for the tables that break simple OCR.

  • Line items

    Invoice and PO line-item extraction

    Capture product, description, quantity, unit, price, tax, amount, requested date, and other row-level values without flattening the document.
  • Multi-column

    Wide and irregular tables

    Understand tables with many columns, inconsistent spacing, wrapped text, or column labels that do not align perfectly across pages.
  • Nested data

    Tables inside tables

    Preserve hierarchy where a parent row contains sub-items, test results, schedules, allocations, or other nested records.
  • Multi-page

    Tables that continue across pages

    Recognize continued tables and preserve logical rows when headings repeat or page breaks interrupt the layout.
  • Multiple tables

    Different tables in one document

    Automatically distinguish multiple table types on the same page or document and map each one to the correct schema.
  • Text to table

    Structure data that is not drawn as a table

    When the document contains repeating business records in paragraphs or text blocks, Artificio can normalize the information into rows and columns for further processing.

How it works

From document tables to structured business records.

Artificio does more than detect rows and columns. It understands which table it is looking at, what each column means, how the table relates to the document header, and where each extracted record belongs next.

  1. 1

    Ingest

    PDF, image, XLS, TXT, scan

  2. 2

    Understand tables

    Detect table type and structure

  3. 3

    Extract rows

    Line items, columns, nested values

  4. 4

    Relate

    Connect header values to rows

  5. 5

    Create Table View

    Validate, transform, automate

Discrepancy detection

Extract the table and inspect the data at the same time.

Table extraction can surface inconsistencies while the data is being structured. That makes the extracted rows immediately more useful for downstream validation and human review.

  • Within-document discrepancies

    Check whether line-item amounts reconcile with quantity × unit price, whether totals match the sum of rows, whether expected columns are missing, or whether duplicated lines appear inside the same document.
    • Example: Quantity 10 × Unit Price $18.00 = $180.00, but extracted line amount = $195.00 → REVIEW

  • Structural anomalies

    Flag unusual row counts, missing table sections, inconsistent units, unexpected nested rows, or content that does not fit the expected table schema.
    • Example: Expected test result + unit + specification, but specification column is missing → REVIEW

Automating something that isn't on this page? The agents adapt to new document types, new systems and new rules. Tell us what you are automating and we will show you the nearest thing we run.

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Header + table intelligence

Keep document context connected to every line item.

Rows rarely make sense without the document header. Artificio connects key-value fields from the parent document to each extracted table record so downstream workflows receive complete business context.

Document headerSupplier Invoice
vendorName
Acme Supply Co.
invoiceNumber
INV-88421
purchaseOrder
4500012345
currency
USD
Extracted table rowLine Item 01Inherited context → vendor + invoice + PO + currency
material
MAT-100
quantity
50
unitPrice
25.00
amount
1250.00

Nested & hierarchical tables

Preserve the relationships inside complex tables.

Some business documents contain a parent row with multiple child records: an inspection characteristic with repeated measurements, an order line with schedule lines, a claim with several adjustments, or a material with multiple test results.

Artificio can retain those relationships instead of flattening everything into one disconnected table.

  1. ViscosityInspection Characteristic: ViscositySpecification: 40–60 cP
  2. measurement-01Measurement 0148.2 cP · PASS
  3. measurement-02Measurement 0250.1 cP · PASS
  4. measurement-03Measurement 0361.4 cP · REVIEW

Table View

Every extracted line becomes a usable record.

Once extraction is complete, Artificio inserts the rows into a Table View. From there, users can review, validate, transform, enrich, filter, compare, or send the records into downstream workflows.

TABLE VIEW · SUPPLIER INVOICE LINE ITEMS3 records
Table View
InvoiceMaterialQtyUnit PriceAmountStatus
INV-88421MAT-10050$25.00$1,250VALID
INV-88421MAT-20020$32.00$640VALID
INV-88421MAT-30010$18.00$195REVIEW

Document types & formats

Extract tables from the documents your business already receives.

Artificio can work with visual documents, spreadsheets, and text-based files, then normalize the extracted information into a common structured table representation.

InvoicesPurchase OrdersInspection ReportsCertificates of AnalysisBills of LadingPacking ListsBank StatementsClaimsSchedulesPrice ListsSpecificationsCustom Documents
PDFJPG / PNGScansXLS / XLSXCSVTXT

What happens next

Table extraction is the structured-data layer.

This page focuses on extracting and structuring table data. Once rows exist in a Table View, other Artificio capabilities can validate, transform, review, or automate them.

FAQ

Common questions about AI table extraction.

Can Artificio extract line items from invoices and purchase orders?
Yes. Artificio can extract row-level values such as material, description, quantity, unit of measure, price, amount, tax, requested date, and other configured fields while preserving the table structure.
Can it extract nested tables?
Yes. Artificio can represent hierarchical relationships such as a parent row with child records, repeated test measurements, schedule lines, or other nested business data.
Can it identify several different tables in the same document?
Yes. Different table structures can be identified and mapped independently rather than forcing all tabular content into one schema.
Can Artificio connect header fields with table line items?
Yes. Header values such as vendor, invoice number, PO number, customer, batch, or currency can be associated with each extracted row so the Table View retains full document context.
What is a Table View?
A Table View is the structured representation created from extracted rows. It can be used for review, validation, transformation, enrichment, filtering, and downstream automation.
Can it detect discrepancies during table extraction?
Yes. Artificio can surface configurable structural or arithmetic inconsistencies and mark affected rows for further review or validation.
Can it create table data from paragraphs or text?
Yes. When unstructured text contains repeating business records or attributes that logically belong in rows and columns, Artificio can normalize that information into structured table records.
What file formats are supported?
The table extraction workflow can process formats such as PDF, images/scans, Excel, CSV, and text files, depending on the configured ingestion and extraction path.

Security & compliance

Structured table data with enterprise controls.

Extracted rows remain connected to their source document and can be reviewed, validated, transformed, and governed before downstream use.

  • ISO 27001
  • SOC 2 TYPE II
  • TABLE VIEW
  • HUMAN REVIEW

See it on your hardest table

Send us a complex table. See Artificio turn it into structured records.

Bring an invoice, PO, COA, inspection report, spreadsheet, or document with nested or multi-page tables. We'll show how Artificio extracts the rows, connects them to the document header, flags discrepancies, and creates a Table View ready for processing.

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