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Description
Defacta conducts verification of text generated by AI or sourced externally, cross-referencing it with reliable sources to identify issues such as hallucinations, unsupported assertions, fabricated references, biases, and manipulative framing techniques. It systematically extracts significant claims from submitted text, URLs, or AI-generated outputs, subsequently validating them against independent sources and established fact-checking databases.
The generated reports encompass findings, metadata of the sources, indicators of risk, and suggested corrective actions, all of which are timestamped and secured with SHA-256 hashes to ensure a reliable audit trail. Users are empowered to modify the text, create prompts for corrections, re-evaluate changes, and perform version comparisons, enhancing the accuracy of their content.
Additionally, reports can be exported in various formats including PDF, DOCX, JSON, Markdown, XLSX, and TXT for versatile usability. The platform offers integration via API, MCP servers, and browser extensions, making it an essential tool for analysts, compliance teams, journalists, and enterprise AI workflows where maintaining high accuracy is of utmost importance. Its comprehensive features ensure that users can effectively manage and verify the integrity of the information they handle.
Description
Docling is a user-friendly, self-sufficient, open-source toolkit licensed under MIT that facilitates the transformation of disorganized documents into structured data, thereby enhancing subsequent document and AI workflows. This versatile tool can interpret a wide array of document types, including PDF, DOCX, PPTX, XLSX, HTML, Markdown, AsciiDoc, CSV, images, audio files, and even scanned documents using any preferred OCR engine. Docling proficiently identifies and processes various elements such as tables, formulas, reading sequences, bounding boxes, headers, footers, images, captions, code snippets, list items, paragraphs, and overall document architecture, which significantly aids in the searchability and integration of the extracted content into AI systems, retrieval-augmented generation, and agent-based applications. Furthermore, it allows for exporting the parsed output in formats like JSON, plain text, Markdown, HTML, and Doctags, thus providing developers with versatile options for their development pipelines and applications. By efficiently organizing and managing components based on reading sequence, Docling breaks down documents into manageable, continuous text segments, optimizing the processing experience.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
Google Sheets
HTML
JSON
Markdown
Microsoft Excel
Model Context Protocol (MCP)
Python
Integrations
Google Sheets
HTML
JSON
Markdown
Microsoft Excel
Model Context Protocol (MCP)
Python
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Defacta
Founded
2026
Country
Israel
Website
defacta.pro/
Vendor Details
Company Name
Docling
Country
United States
Website
www.docling.ai/
Product Features
Product Features
OCR
Batch Processing
Convert to PDF
ID Scanning
Image Pre-processing
Indexing
Metadata Extraction
Multi-Language
Multiple Output Formats
Text Editor
Zone Selection Tool