This startup offers an AI-powered platform that converts unstructured documents, including images and PDFs, into searchable and structured data. The platform analyzes documents for custom requirements, including fraud detection and data extraction, enabling users to gain insights and automate document processing.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations across various industries struggle with the time-consuming and error-prone process of manually extracting data and identifying discrepancies within unstructured documents like PDFs, images, and scanned files. This manual review process is particularly challenging when dealing with large volumes of documents, leading to delays, increased operational costs, and potential compliance issues.
Solution
Discrepancy AI offers an AI-powered platform that automates the extraction of data from unstructured documents, transforming them into searchable and structured data in formats like JSON and CSV. The platform utilizes a custom AI vision system, Optic AI, to accurately extract information from various document types, including financial records, legal contracts, and insurance claims. It enables users to organize, filter, and analyze documents, identify patterns, and detect anomalies, inconsistencies, errors, and potential fraud. The platform also supports custom extraction requests using natural language, eliminating the need for templating and allowing users to tailor the analysis to their specific requirements.
Target Audience
The primary target audience includes organizations in industries such as real estate, insurance, finance, and legal, as well as legal teams, that handle large volumes of documents and require efficient and accurate data extraction and analysis.
Features
- AI-powered data extraction from unstructured documents, including images, PDFs, and scanned files
- Custom AI vision (Optic AI) for accurate information extraction
- Automated detection of anomalies, inconsistencies, errors, and fraud
- Custom extraction requests using natural language, eliminating the need for templating
- Document organization, filtering, and analysis capabilities
- Support for various document types, including financial records, legal contracts, and insurance claims
- API integration for seamless integration with existing systems
- Output of structured data in JSON and CSV formats