platoseedplatoseed
The complete agentic document platform
Reducto is the agentic document platform for leading AI teams building systems to automate document workflows at enterprise scale. Our platform provides a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows. Reducto is trusted by leading AI teams at companies like Harvey, Scale AI, and Vanta. We are built for enterprise workloads with flexible deployment options from the cloud to fully air-gapped environments, SOC II and HIPAA compliance, and zero data retention. Learn more: https://reducto.ai/ Find our YC deal: https://reducto.ai/yc
Reducto is an agentic document platform designed for AI teams to parse, extract, and manage documents at enterprise scale. It emphasizes a multi-pass OCR and vision-language model approach to deliver structured data with high accuracy across diverse document types.
Reducto provides a unified platform with APIs for parsing documents, extracting structured data with schema-level precision, and editing detected data across PDFs, images, forms, and multi-page documents. It uses a multi-pass system combining OCR and vision-language models to read documents like humans, splits multi-document files automatically, and supports layout-aware extraction, real-time output correction, and multilingual processing. The platform also offers features such as layout extraction, file-type and language support, intelligent chunking, embedding optimization, and image/OCR capabilities for various content types, all accessible via a single API.
Who it’s for: AI teams in enterprises and high-scale organizations across industries that require accurate document processing for finance, healthcare, legal, and related sectors.
Marketing emphasis on enterprise deployments and trials (Try for free, request a demo); mentions of enterprise-scale customers and growth in processed pages indicate traction and growth activity.
Co-founder/CEO at Reducto. Before Reducto I studied CS at MIT, made Ads/Search things as a PM for Google, did ML research at MIT's Media Lab, and spent an unreasonable amount of time playing Pokemon Showdown.
Co-founder/CTO at Reducto. Before Reducto I studied CS at MIT, founded/scaled a comp. chem consulting company to 200k ARR, published computer vision papers with 100+ citations before finishing high school, and spent a little too much time shit posting on Twitter.
Our API allows you to convert complex, unstructured documents into structured outputs that are perfect for RAG, process automation, and more.
Reducto builds an API that converts unstructured enterprise documents (e.g., PDFs) into structured outputs suitable for RAG, process automation, and retrieval pipelines. The launch presents the product, its ability to extract text, tables, and fields from complex layouts, convert graphs to tables, and summarize images, targeted at teams in insurance, healthcare, and finance handling high-volume document workflows.
From the original launch (Jan 2024) — may be outdated.
Formerly “Remembrall” · why startups rename →
Java-native multi-agentic AI operating system for enterprise
AI-enabled M&A deal origination
