RAGFlow
Open-source RAG engine for document understanding and AI search
ragflow.io ↗📍 Shanghai, China
Verified Data
“Based on 12 employees and Early Stage VC funding in 2025, typical open-source + enterprise SaaS model suggests $500K-$2M ARR range”
“the company's latest financing was an Early Stage VC round on April 1, 2025”
“Monthly web traffic for ragflow.io was 88,133 visits as of February 12, 2026”
“The RAGFlow GitHub repository, `infiniflow/ragflow`, demonstrates significant community engagement with 74.5k stars and 8.3k forks”
“InfiniFlow has a team size of 12 employees”
“Monthly web traffic for ragflow.io was 88,133 visits as of February 12, 2026, with a month-over-month change of -4.18%”
Company Profile
Contact
@infiniflowaiStrategic Analysis
Strategy
Open-source first approach with RAGFlow as the core product, building community adoption through GitHub while developing commercial enterprise features. Targeting multiple verticals including finance, healthcare, manufacturing, education, and government sectors for monetization.
Tactics
Heavy investment in open-source community building via GitHub (74.5k stars), maintaining active development with regular releases. Building enterprise features on top of open-source core for commercial monetization across regulated industries.
Competitive Positioning
Positioned as an open-source alternative in the RAG engine space, differentiating through community-driven development and enterprise-ready features for regulated industries like finance and healthcare.
Marketing Approach
Developer-first marketing through open-source GitHub repository and community engagement. Technical content marketing with regular product updates and conference participation to build brand awareness in AI/ML community.
Notable
74.5k GitHub stars, targeting regulated industries
Tech Stack
Python
TypeScript
C++
GoCShellRelated AI Developer Tools Companies
Discovery Sources
Signals
“Monthly web traffic for ragflow.io was 88,133 visits as of February 12, 2026, with a month-over-month change of -4.18%”
“The RAGFlow GitHub repository, `infiniflow/ragflow`, demonstrates significant community engagement with 74.5k stars and 8.3k forks”
“the company's latest financing was an Early Stage VC round on April 1, 2025”
“Its estimated monthly website traffic is 88,133 visits as of February 12, 2026”
“showing a slight decrease of -0.0418035% month-over-month”
“RAGFlow's GitHub repository, infiniflow/ragflow, boasts 74.5k stars and 8.3k forks”
“While specific total funding raised remains undisclosed, RAGFlow's parent company, InfiniFlow, is venture capital-backed”
“The company has completed both a Seed Round (September 27, 2023) and an Early Stage VC round (April 1, 2025), the specific amounts for total funding raised and current revenue or MRR are not disclosed in the available information”
“According to Semrush, the ragflow.io website received an estimated 91.98K visits in December 2025”
“its organic search traffic increased by 42% month-on-month”
Evidence
OpenRAG is a comprehensive, single package Retrieval-Augmented Generation platform built on Langflow, Docling, and Opensearch.
OpenRAG is a comprehensive, single package Retrieval-Augmented Generation platform built on Langflow, Docling, and Opensearch.
Accelerate your AI-Readiness by 95%.
Trusted AI answers with citations, deployed in days
RAG‑LCC is an experimental Retrieval‑Augmented Generation (RAG) lab focused on understanding and controlling retrieval and context assembly under real‑world constraints: limited context windows, modest GPUs, large documents, and multi‑turn chat.