The API returns structured tabular data extracted from PDF documents. This includes multiple tables, each represented as an array in JSON format, with options to receive the data in Excel (.xlsx) or CSV formats.

The response includes key fields such as `tableIndex`, `pageRange`, `rows`, `rowCount`, `columnCount`, `strategyUsed`, and `confidence`. Each table's data is organized to facilitate easy programmatic processing.

The response data is organized into a summary section that includes the total number of tables and pages, followed by an array of tables. Each table contains its rows, page range, and confidence score, making it easy to navigate and utilize.

The primary parameter for the endpoint is the PDF file itself, which can be uploaded directly. Additional parameters may include options for output format (JSON, Excel, CSV) and settings for confidence scoring.

Data accuracy is maintained through deterministic output, meaning the same input consistently produces the same result. The API also provides optional confidence scores for each table, indicating the reliability of the extraction.

Typical use cases include extracting invoice line items, converting financial reports into structured datasets, automating data pipelines, and ingesting tabular data from customer-uploaded PDFs, streamlining data processing workflows.

Users can leverage the structured output for integration into data pipelines, ETL processes, or backend systems. The organized format allows for easy manipulation and analysis of the extracted tables in various applications.

Users can expect data patterns that reflect the original table structure, including row and column alignment. The API handles irregular tables and empty cells, ensuring that the output remains structured and usable for further processing.

The API can extract various types of structured tables, including those with irregular layouts, empty cells, and uneven rows. It automatically detects single or multiple tables within a PDF, ensuring that only grid-based tabular structures are processed.

The API supports tables that span multiple pages, accurately capturing the entire table structure and returning it in a single output. Each table's page range is included in the response for easy reference.

Yes, users can customize their data requests by specifying the desired output format: JSON, Excel (.xlsx), or CSV. This flexibility allows integration into various applications and workflows.

The API offers optional confidence scores for each extracted table, indicating the reliability of the extraction. This feature helps users assess the quality of the data returned.

The API is designed to be stateless and privacy-friendly, ensuring that no data is stored after processing. It uses secure HTTPS-only communication to protect user data during transmission.

Users can expect the API to handle empty cells gracefully, preserving the overall structure of the table. The output will reflect the original layout, allowing for straightforward data manipulation despite any missing values.

Confidence scores range from 0 to 1, indicating the likelihood that the extracted table is accurate. A higher score suggests greater reliability, helping users determine which tables to trust for further processing.

The `strategyUsed` field indicates the method employed by the API to extract the table data. This information can help users understand the extraction process and assess the suitability of the output for their specific needs.

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