What Ragie AI does

Ragie AI operates a fully managed Retrieval-Augmented Generation (RAG) platform sold to developers and AI builders as infrastructure. The service handles the entire RAG pipeline — document ingestion, multimodal parsing (text, PDFs, images, audio, video), intelligent chunking, indexing across vector, keyword, and summary stores, and hybrid retrieval with LLM re-ranking — exposed via a REST API and TypeScript/Python SDKs. The platform layers proprietary capabilities on top of this base, including an Agentic OCR service (Ragie Parse) that extracts structured elements with bounding-box traceability, a multi-agent deep-search engine (Agentic Retrieval) that decomposes queries and emits verifiable citations, a context-aware MCP Server for AI agents, and 20+ native OAuth connectors (Google Drive, Notion, Confluence, Slack, Salesforce, etc.) for automatic data sync.

Ragie monetizes through tiered subscriptions — Free, Starter, Pro, and custom Enterprise — with usage-based overage on document pages and audio/video processing, plus a separately priced end-user chatbot product (Base Chat) at $18/seat/month. Distribution is product-led and developer-first (self-serve signup, free tier, CLI, SDKs, open-source repositories, Discord community), with an enterprise sales-assisted motion for VPC deployments and SOC 2 / HIPAA / GDPR / CCPA-compliant workloads. Customers span startups (Ellis, Vambe, Glue, Supergood.ai, Takeoff AI) and enterprise platforms (Zapier, Make.com, Advantest, Appsmith, Eigen Labs, Crypto Counsel/Crystal), with documented outcomes such as 5–10x faster legal drafting, 3-week vs 3-month delivery timelines, and 91% accuracy on FinanceBench.

The company was founded in August 2024 in San Francisco as a spin-out from Glue, raising a $5.5M seed round led by Craft Ventures with Saga VC, Chapter One, and Valor. It employs 11–50 people and has not disclosed a subsequent funding round or ARR.

Name

Ragie AI

Legal name

ragie Corp

Website

https://ragie.ai

Company type

Private

Founded year

2024

Operating status

Operating

Headcount range

11–50 employees

Short description

Ragie AI provides a fully managed Retrieval-Augmented Generation (RAG) platform that handles document ingestion, multimodal indexing, and hybrid retrieval for developers building context-powered AI applications, with separate end-user chatbot product Base Chat.

Ownership category

akta.pro rank

Product category

AI Retrieval Infrastructure

NAICS

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518), Web Search Portals and All Other Information Services (519290)

SIC

Services-Prepackaged Software (7372)

akta.pro primary industry

Retrieval-Augmented Generation (RAG), Vector Databases & Knowledge Grounding (HDAAACAE)

akta.pro secondary industries

Question Answering & Retrieval-Augmented Generation (RAG) (HDAAADAC), Generative AI & LLM Solutions Services (RAG, Agents, Copilots) (BPAEAHAG)

Keywords

• RAG-as-a-Service
• Document ingestion
• Vector retrieval
• AI context engine
• Multimodal indexing

Headquarters

HQ city

San Francisco

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Infrastructure, Marketing or Sales, Operations

Revenue model

1. RAG-as-a-Service Platform Subscription: Subscription-based pricing with tiered plans (Free, Starter, Pro, Enterprise) based on document pages, audio/video processing hours, and feature access. Revenue derives from monthly/annual subscription fees and usage overages on paid tiers.
2. Usage-Based Overage Charges: Plans include allocated page processing quotas and media processing limits. Overage charges apply when usage exceeds plan allocations (e.g., page processing limits, media streaming limits, retrieval limits).
3. Base Chat (End-User Application): Base Chat, Ragie's own chat application powered by its RAG platform, is offered as a separate product at $18/user/month with Starter ($100/month) and Pro ($450/month) data plan add-ons, representing a consumer/SaaS application revenue stream.
4. Enterprise / Custom Contracts: Enterprise plan with custom pricing for organization-wide deployment. Includes VPC deployment, single-tenant deployment options, custom data plan allocations, and dedicated support—likely negotiated annual or multi-year contracts.

Pricing tiers

Go-to-market motion4 records

Distribution channels4 records

Marketing channels10 records

Core offering

Ragie provides a fully managed RAG-as-a-Service platform for developers, handling the complete retrieval-augmented generation pipeline from document ingestion and multimodal indexing (text, PDFs, images, audio, video) through hybrid retrieval to entity extraction and agentic deep-search. The platform is exposed via REST APIs, TypeScript and Python SDKs, and a context-aware MCP server, with 20+ pre-built native OAuth connectors to data sources such as Google Drive, Notion, Confluence, Salesforce, and Slack.

Product overview

Ragie is a fully managed RAG-as-a-Service platform (a single unified product offering, not a modular platform-plus-modules architecture) that provides intelligent indexing and retrieval APIs for developers building context-powered AI applications. The core Ragie Platform handles document ingestion, multimodal indexing (text, PDFs, images, audio, video), and retrieval pipeline with hybrid search. Key integrated features include: Advanced RAG Engine for hybrid semantic-keyword search with re-ranking and summary indexing; Agentic Retrieval for multi-step query reasoning with citations; Ragie MCP Server providing context-aware tool descriptions for AI agents; Ragie Parse for agentic OCR extracting structured elements with bounding boxes; Ragie Connect for native data source connectors (Google Drive, Notion, Confluence, Salesforce, etc.); and Partitions for multi-tenant data isolation. Base Chat is a separate consumer-facing chatbot product built on the Ragie platform.

Differentiator

Problem solved

Functional benefit

Brands

• Base Chat: A chat application that enables teams to search their knowledge base across multiple data sources including Google Drive, Notion, Jira, PDFs, slides, audio, and video.
• Ragie Parse
• Ragie Connect

Products and services

• Ragie Platform (RAG-as-a-Service) Fully managed Retrieval-Augmented-Generation platform that handles the complete pipeline from document ingestion through multimodal indexing (text, PDFs, images, audio, video) to hybrid retrieval combining vector, keyword, and summary indexes, plus entity extraction. Sold via a free tier, paid Starter and Pro subscriptions with usage-based overages, and custom Enterprise contracts with VPC deployment, SOC 2 Type II, HIPAA, GDPR, and CCPA compliance. Target buyers are developers and enterprise teams building AI applications, agents, and assistants powered by their own data.
• Base Chat Ready-to-use AI chatbot application built on the Ragie platform that lets teams query a shared knowledge base across connected data sources including Google Drive, Notion, Jira, PDFs, slides, audio, and video. Distributed as a hosted SaaS product with a 7-day free trial and a per-seat subscription of $18/user/month with Starter and Pro data plan add-ons; also available as an open-source self-hosted option.

Quantifiable outcome

• 5-10x faster legal drafting (Ellis case: reduced from 1-2 days to minutes)
• +6 more outcomes

Named customers8 records

Segments7 records

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration17 records

AI capability11 records

Feature9 records

Scale indicators4 records

Recent moves6 records

Expansion highlights6 records

Direct peers

• Pinecone: Pinecone is a managed vector database purpose-built for similarity search and the data layer behind RAG applications. It is the closest direct competitor to Ragie's managed retrieval infrastructure, with significant overlap in customer base (AI application developers) and overlap in capability on vector indexing and hybrid retrieval.
• Weaviate: Weaviate is an open-source and managed vector database with built-in hybrid (vector + keyword) search and module integrations for embedding models. It competes head-to-head with Ragie on the managed retrieval/vector store layer for RAG workloads, particularly for developers wanting hybrid search and self-hosted options.
• Qdrant: Qdrant is an open-source vector database with a managed cloud offering, focused on high-performance similarity search and filtering. It is a direct managed alternative to Ragie's vector indexing layer, frequently benchmarked and chosen by RAG application developers.
• Chroma: Chroma is an open-source embedding database widely used for LLM applications and RAG pipelines. It is a direct peer to Ragie on the developer-facing vector store and retrieval tooling, with a strong open-source community and managed Chroma Cloud offering.
• Vectara: Vectara is a managed RAG platform offering retrieval, grounding, and hallucination mitigation as an API for enterprise developers. It is a direct competitor to Ragie's managed RAG-as-a-Service value proposition, with similar positioning around accuracy and enterprise compliance.
• LlamaIndex: LlamaIndex is a leading open-source framework for building RAG and agentic data pipelines, with a hosted LlamaCloud service. It directly competes with Ragie as the alternative path developers choose between "assemble open-source RAG yourself" and "use Ragie's managed service."
• LangChain: LangChain is the dominant open-source framework for LLM application and RAG orchestration, with a hosted LangSmith platform. It overlaps with Ragie as the primary developer toolkit for assembling retrieval pipelines, and as a competing platform-plus-managed-service offering via LangChain/LangSmith.

Broad incumbents

• Cohere: Cohere is a foundation-model provider that has expanded into enterprise RAG offerings (Cohere Compass, RAG kits) with retrieval and grounding features. It competes with Ragie on the enterprise retrieval layer from a much larger, broader AI platform position with proprietary models.
• Amazon Bedrock Knowledge Bases: AWS Bedrock's Knowledge Bases and Amazon Kendra provide managed RAG and enterprise search built into the AWS ecosystem. They are broad incumbent offerings that overlap with Ragie's retrieval-as-a-service for enterprises already standardized on AWS.
• Azure AI Search: Azure AI Search (formerly Cognitive Search) offers hybrid vector + keyword retrieval and is integrated across Microsoft Fabric, Copilot, and Azure OpenAI. It is a broad incumbent managed retrieval platform that competes with Ragie for enterprise RAG workloads, especially inside Microsoft shops.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• Xx.com/ragieai
• GitHubgithub.com/ragieai
• LinkedInlinkedin.com/company/ragie

Compliance4 records

Revenue estimate

Valuation estimate

Number of profiles

Profiles2 records

Funding overview

Funding rounds1 record

Investors4 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Ragie AI