Reducto utilizes advanced parsing algorithms to convert unstructured documents into structured, LLM-ready data, ensuring high accuracy across complex layouts such as tables, forms, and graphs. This technology enables businesses to extract critical insights efficiently while maintaining strict data security protocols, including zero data retention options.
Funding
$8.9M 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.
BKTFounders
Product
Problem
Many organizations struggle to efficiently extract structured data from unstructured documents like PDFs, especially those with complex layouts such as tables, forms, and graphs. This makes it difficult to leverage the information within these documents for downstream applications, including large language models (LLMs).
Solution
Reducto provides a document parsing API that converts unstructured documents into structured, LLM-ready data. The platform utilizes advanced parsing algorithms to ensure high accuracy across complex layouts. Reducto optimizes document outputs, including interpreting graphs and intelligently chunking content, to create inputs suitable for LLMs. The API allows users to define custom schemas, enabling precise extraction of the content that matters most to their business.
Target Audience
Reducto targets startups and enterprises in industries such as legal, finance, and insurance that need to accurately ingest unstructured data from documents.
Features
- High accuracy parsing of tables, forms, images, and graphs within documents
- LLM-ready outputs optimized for various use cases
- Custom schema definition for precise content extraction
- Zero data retention option via hosted API
- Option for self-hosting models in a private cloud or on-premise environment
- Comprehensive benchmark for PDF table parsing