TableFlow Extract Clean Data from Messy Spreadsheets

What is TableFlow?

TableFlow leverages Artificial Intelligence to automate the extraction and processing of data from complex documents, including messy spreadsheets, PDFs, and images. It streamlines workflows by replacing manual data entry, cleaning, and reconciliation processes. The platform connects with multiple leading AI providers such as OpenAI, Anthropic, Amazon Bedrock, Mistral, and Gemini, selecting the optimal model for each specific file and task to ensure high accuracy.

The system is built to handle large volumes of documents, offering robust scaling capabilities. It features AI-driven extraction capable of reading complex layouts, applies intelligent rules for data transformation, and includes built-in validation steps to flag potential issues. An intuitive review interface allows for human oversight and correction, ensuring data integrity before integration into other systems via API, direct connections, or file exports.

Features

AI-Powered Data Extraction: Utilizes AI to accurately extract data from complex layouts in spreadsheets, PDFs, and images.
Automated Data Transformation: Transforms extracted data using templates and intelligent rules for consistency.
Built-in Data Validation: Includes validation steps to automatically flag potential data issues.
Human-in-the-Loop Review: Provides an intuitive interface for users to quickly review and correct flagged data.
Multi-AI Model Support: Connects with various AI providers (OpenAI, Anthropic, Bedrock, etc.) to select the best model per task.
Flexible Data Ingestion: Supports drag-and-drop uploads, cloud drive connections, and API integration.
Seamless Integration: Allows cleaned data integration via API, ERP/CRM connections, or CSV/JSON exports.

Use Cases

Automating data entry from diverse document formats.
Cleaning and structuring data from messy spreadsheets.
Processing high volumes of business documents like purchase orders and packing lists.
Reducing manual effort in data reconciliation and validation.
Improving data accuracy for operational reporting and analysis.
Scaling document processing workflows efficiently.
Streamlining onboarding processes involving document data capture.