ragie

ragie

Ragie is a fully managed RAG-as-a-Service (context engine) that ingests, parses, indexes, and retrieves multimodal content to power agents, assistants, and apps via purpose-built APIs and SDKs for developers and enterprises.

ragie is ai agents software teams evaluate for education & research. Use this page to review pricing, integration signals, and the best alternatives before you commit.

Freemium API Enterprise 75/100
#477 in AI Agents (477 tools)
Just launched
Data reviewed Aug 19, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: Education & Research

What it does

AI Agents software for decision-makers comparing workflow fit and alternatives.

Best fit

Education & Research

Pricing snapshot

Freemium from Not listed (free tier available for developers to get started)

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ragie

Ragie is a fully managed RAG-as-a-Service designed to provide agent-ready context for assistants, agents, and apps. It ingests multimodal data (text, PDFs, images, audio, video), parses documents (including tables, forms, charts), extracts structured entities, and builds multiple indexes (vector, keyword, summary) so applications can retrieve accurate and relevant context via APIs and SDKs. Ragie targets developers and enterprises who need reliable, production-grade retrieval and context management, offering connectors to common data sources, enterprise deployment options (cloud, VPC, on-prem), and compliance certifications to support regulated workloads.

Ragie is a managed RAG service for developers to build generative AI applications.

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Key Features

Multimodal Ingestion

Handles text, PDFs, images, audio, and video through a unified pipeline so all content types are parsed, chunked, and indexed automatically.

Indexing & Retrieval

Builds vector, keyword, and summary indexes and runs a combined retrieval pipeline (hybrid semantic-keyword search) with reranking to surface the most accurate context.

Agentic OCR / Document Parsing

Agentic OCR extracts structured elements from any document, including tables, forms, charts, and key-value pairs, with precise bounding boxes for traceability.

Entity Extraction

Plain-language-driven extraction: tell Ragie what to extract and it pulls structured entities from documents for precise, contextual data.

Native Connectors

Pre-built connectors and OAuth integrations for sources like Google Drive, Notion, Confluence, Slack, and more to keep context current via automatic sync.

MCP Server & Agentic Retrieval

Context-aware MCP server provides permissioned access and agentic retrieval for multi-step reasoning and intelligent tool use.

Partitions & Multi-Tenancy

Securely isolate data by tenant, workspace, or customer to prevent leakage and improve retrieval relevance at scale.

Enterprise Deployments & Security

Deployment flexibility (cloud, VPC, on-prem) with enterprise-grade compliance (SOC 2 Type II, GDPR, HIPAA, CCPA) and AES-256/TLS encryption.

Developer Tools & SDKs

APIs, SDKs, docs, and a developer-focused DX to accelerate integration and deployment of RAG pipelines.

Pricing

Free Tier Available

Free tier available for developers to get started building applications.

Free

Not listed (free tier available for developers to get started)
  • Developer free tier to start building

Starter

Not listed (see pricing page)
  • Designed for small projects

Pro

Not listed (see pricing page)
  • Production-grade plan

Enterprise

Not listed (contact sales)
  • Scale, compliance, and custom deployments

Use Cases

Legal Research & Drafting

High-recall retrieval and precise extraction accelerate legal drafting and research, helping legal teams capture relevant details and reduce risk.

Internal Knowledge Assistants

Power enterprise assistants that surface company-specific knowledge from Google Drive, Notion, Confluence, and other sources for faster decision-making and fewer blockers.

Sales & Customer-facing Tech

Enhance sales workflows with precise retrieval from product data, customer interactions, and reviews to enable personalized customer interactions and faster insights.

Production RAG for Developers

Developers building RAG-enabled applications (chatbots, SaaS features, agentic apps) can offload ingestion, chunking, indexing, and retrieval to Ragie to reduce infrastructure complexity.

Integrations

Google Drive

Sync files and documents via OAuth to keep context current automatically.

Notion

Connect Notion workspaces to ingest notes, docs, and structured content for indexing.

Confluence

Sync Confluence content for enterprise knowledge retrieval.

Slack

Connect Slack to ingest messages and context for assistants and agents.

Benefits

Speeds development and time-to-deployment by providing managed ingestion, chunking, and indexing.
Improves retrieval accuracy using hybrid vector/keyword/summary indexes plus LLM re-ranking and entity extraction.
Enterprise-ready security and compliance (SOC 2 Type II, GDPR, HIPAA, CCPA) with strong encryption and flexible deployment.
Automatic syncing via native connectors keeps context up to date without custom pipelines.
Reduces maintenance burden compared to building and operating an in-house RAG pipeline.

Limitations

Ragie service will end on July 19 (the site includes a notice about service termination); users should contact [email protected] for assistance.
The public site references pricing tiers but does not publish specific price amounts—detailed pricing requires visiting the Pricing page or contacting sales.

Frequently Asked Questions

What is Ragie?
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, offering simple APIs and SDKs and built-in capabilities like summary indexing, chunk reranking, flexible vector filtering, and hybrid semantic-keyword search.
Why should you use Ragie?
Ragie removes the complexity of building and maintaining production RAG pipelines — handling connectors, chunking, indexing, retrieval, and anti-hallucination features so developers can focus on building applications instead of infrastructure.
Who should use Ragie?
Developers building AI applications that leverage proprietary data for accurate outputs — internal chatbots, enterprise SaaS products, and any application requiring context-rich AI — from startups to enterprises.
How does Ragie keep my data secure?
Ragie is SOC 2 Type II, GDPR, HIPAA, and CCPA compliant, uses AES-256 encryption at rest and TLS in transit, supports flexible deployments (cloud, VPC, on-prem), and states it does not use customer data for training.
How much does Ragie cost?
Ragie offers a free tier plus Starter, Pro, and Enterprise plans; specific pricing details are available on the Pricing page or by contacting sales.

Getting Started

  1. 1 Step 1: Start for free or book a demo to create an account.
  2. 2 Step 2: Connect data sources via pre-built connectors (Google Drive, Notion, Confluence, Slack) or upload files via API.
  3. 3 Step 3: Ingest — Ragie parses, chunks, and indexes content (text, PDFs, images, audio, video) automatically.
  4. 4 Step 4: Deploy — Use the retrieval, extraction, or structured data APIs/SDKs to integrate context into your application.

Support

email

[email protected] for assistance and trust center access.

sales

Contact sales (link on site) for Enterprise inquiries and deployment options.

docs

Documentation, SDKs, and developer resources available via the Ragie website (Docs link).

community

Discord listed as a community channel on the site.

API

Available: Yes
Documentation:

API and SDK documentation available via the Ragie website (Docs link).

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