RedShred is an API-first platform that transforms unstructured document data into structured, searchable information using natural language processing and computer vision. This technology enables developers and data scientists to quickly access and utilize critical data from various document formats, eliminating the inefficiencies of manual data extraction.
Funding
$893.5K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations struggle to efficiently extract and structure data trapped within unstructured documents like PDFs, scanned images, and spreadsheets. Manual data extraction is time-consuming, error-prone, and hinders the ability to leverage document-based information for analytics, model building, and application development. This results in delayed insights and inefficient workflows.
Solution
RedShred offers an API-first, documents-as-a-database platform that automatically transforms unstructured document data into structured, searchable information. By leveraging natural language processing (NLP) and computer vision, the platform extracts content, enriches it with metadata, and reshapes it into a usable format. This allows data scientists and developers to quickly access and utilize critical data from various document types, eliminating the need for manual data extraction and enabling the creation of smarter applications. The platform treats documents as a database, providing structured and searchable data that can be easily integrated with existing systems.
Target Audience
The primary target audience includes data scientists and developers who need to extract, structure, and utilize data from unstructured documents for building models and applications.
Features
- Easy Document Upload API for uploading documents into Collections
- Supports common document formats such as scanned images, PDFs, spreadsheets, and plaintext
- Tailored configuration for targeted extraction and enrichment based on document types
- API endpoints return structured JSON data for easy integration with existing platforms
- Extracts page content using NLP and computer vision
- Attaches metadata to page segments and indexes the data
- Enables structured and semantic search across documents
- Facilitates the creation of layers of interconnected metadata