Ragie
Meet Ragie.
Powered by the most advanced RAG pipeline, Ragie uses context engineering to deliver fast, accurate, context-rich retrieval—through structured chunking, multi-layered indexing, and LLM-aware optimizations—built for production-grade generative AI. Ragie is built for enterprise-scale workloads with multi-tenant architecture, SOC 2-compliant security, and seamless performance at any scale. Built to handle any data you throw at it — Ragie’s multimodal ingest pipeline processes text, PDFs, images, audio, video, tables, and more. It parses, enriches, and structures diverse content into a unified format ready for chunking, indexing, and retrieval. Ragie offers out-of-the-box features that accelerate your application development. Built to meet the security, scale, and reliability requirements of production AI. Seamless data ingest with built-in authentication and authorization Ragie’s fully-managed connectors handle authentication and authorization to securely access data from popular data sources, freeing up precious engineering time and resources. Automatic syncing keeps data up to date Automatic syncing keeps your RAG pipeline up to date, ensuring your application delivers accurate and reliable information around the clock. Growing library of native integrations Purpose-built for AI applications, Ragie’s growing list of native connectors allow seamless integration with the most popular data sources. Connect your data (or your customers’) to your app, no matter where it lives. With Ragie Connect, your customers can securely connect and manage their own data, directly from your application. For white-label version, chat with sales. Ragie is a fully managed RAG-as-a-Service designed for developers to streamline the ingestion, chunking, and multimodal indexing of structured and unstructured data. It offers simple APIs and SDKs, seamless integration with sources like Google Drive, Notion, and Confluence, and built-in capabilities like summary indexing, chunk reranking, flexible vector filtering, and hybrid semantic-keyword search. With agentic retrieval for multi-step reasoning and a context-aware MCP Server that enables intelligent tool use, Ragie helps your applications deliver state-of-the-art, agent-ready generative AI. Building production applications using RAG can be very tedious. Developers must connect and sync multiple data sources, extract meaningful data from various file formats, implement evolving techniques for chunking and retrieval, build a scalable and resilient data processing pipeline, avoid hallucinations, and ensure content accuracy. Using open-source frameworks can be time-consuming and often results in brittle applications. Originally developed for Glue, Ragie solves this by providing a fully managed RAG-as-a-Service platform. Ragie is ideal for developers who want to build AI applications that leverage their own data for accurate and relevant outputs. Whether you're working on internal chatbots, enterprise SaaS p
Google Document AI
The Document AI solutions suite includes pretrained models for document processing, Workbench for custom models, and Warehouse to search and store.
Create document processors that help automate tedious tasks, improve data extraction, and gain deeper insights from unstructured or structured document information. Document AI helps developers create high-accuracy processors to extract, classify, and split documents. Seamlessly connect to BigQuery, Vertex Search, and other Google Cloud products Enterprise-ready, along with Google Cloud's data security and privacy commitments Built for developers; use the UI or API to easily create document processors Use generative AI to extract data or classify documents out of the box, with no training necessary to get started. Simply post a document to an enterprise-ready API endpoint to get structured data in return. Document AI is powered by the latest foundation models, tuned for document tasks. Also, with powerful fine-tuning and auto-labeling features, the platform offers multiple paths to reach the required accuracy. Structure and digitize information from documents to drive deeper insights using generative AI to help businesses make better decisions. Extract data from your documents using generative AI. For full product capabilities head to Document AI in the Google Cloud Console. Document AI Workbench provides an easy way to build custom processors to classify, split, and extract structured data from documents. Workbench is powered by generative AI, which means it can be used out of the box to get accurate results across a wide array of documents. Furthermore, you can achieve higher accuracy by providing as few as 10 documents to fine-tune the large model—all with a simple click of a button or an API call. With Enterprise Document OCR, users gain access to 25 years of optical character recognition (OCR) research at Google. OCR is powered by models trained on business documents and can detect text in PDFs and images of scanned documents in 200+ languages. The product can see the structure of a document to identify layout characteristics like blocks, paragraphs, lines, words, and symbols. Advanced features include best-in-class handwriting recognition (50 languages), recognizing math formulas, detecting font-style information, and extracting selection marks like checkboxes and radio buttons. Try Document OCR now for accurate text and layout extraction. Developers use Form Parser to capture fields and values from standard forms, to extract generic entities, including names, addresses, and prices, and to structure data contained in tables. This product works out of the box and does not require any training or customization and is useful across a broad range of document customization. Explore document processing with Form Parser. Try out pretrained models for commonly used document types including W2, paystub, bank statement, invoice, expense, US driver license, US passport, and identity proofing. Explore pretrained options in the processor gallery. Document AI is helping customers improve fraud detection, automate customer support, and pro
Ragie
Google Document AI
Ragie
Pricing found: $100 / month, $500 / month, $500 / month, $0.02 / page, $0.02 / page
Google Document AI
Pricing found: $300, $1.50, $0.60, $6, $6
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Ragie
Google Document AI