Enterprise
Retrieval Augmented
Generation Platform
Deploy production-ready RAG pipelines with multi-provider AI support, hybrid search, and enterprise security. No Python required.
Documents
12.4k
Queries
89.2k
Avg Latency
187ms
Uptime
99.9%
Ready to answer questions from 12.4k indexed documents
Powered by Industry-Leading Technology
Enterprise-Grade RAG Pipeline
Everything you need to build production-ready retrieval-augmented generation systems.
Document Ingestion
Parse PDF, DOCX, TXT, Markdown, HTML, CSV, and images with OCR. Automatic chunking and embedding.
Hybrid Search
Combine vector search with BM25 or Elasticsearch. Semantic + keyword for optimal relevance.
Semantic Search
Understand meaning, not just keywords. Multi-provider embeddings for accurate retrieval.
Query Rewriting
Automatic query expansion, HyDE, and multi-query generation for better recall.
Multi-Vector Retrieval
Parent-child chunking, MMR diversification, and metadata filtering for precision.
Streaming Responses
Real-time streaming with markdown rendering, code highlighting, and source citations.
Source Citations
Every answer includes verified sources, confidence scores, and document references.
Hallucination Detection
Real-time groundedness checking, citation validation, and faithfulness scoring.
Evaluation Pipeline
RAGAS metrics: faithfulness, answer relevancy, context precision, and recall.
Multi-Provider AI
OpenAI, Claude, Gemini, DeepSeek, Ollama. Switch providers from the UI.
Authentication
Email, Google, GitHub login with Better Auth. RBAC and workspace support.
Enterprise Security
Encrypted API keys, audit logs, rate limiting, CSRF protection, and input validation.
How It Works
End-to-end RAG pipeline from document upload to verified answers.
Upload Documents
PDF, DOCX, TXT, MD, HTML, CSV, Images
Parsing
Extract text and metadata
Chunking
Semantic / Recursive / Parent-Child
Embeddings
Multi-provider vector generation
Vector Database
Qdrant / Pinecone / Chroma
Retriever
Hybrid search + BM25 + MMR
Reranker
Jina / Cohere / BGE / Cross-Encoder
LLM
OpenAI / Claude / Gemini / DeepSeek / Ollama
Answer with Citations
Sources + confidence + streaming
Interactive RAG Playground
Upload a document and ask questions. See the full RAG pipeline in action.
Upload Document
Try an example
Welcome to the OmniRAG playground! Upload a document or try an example question to see RAG in action.
Multi-Provider AI Support
Switch between leading AI providers without changing your code.
OpenAI
text-embedding-3-small / 3-large
Claude
OpenAI compatible
Gemini
embedding-001
DeepSeek
text-embedding-ada-002
Ollama
nomic-embed-text / mxbai-embed
Enterprise-Grade Features
Built for production workloads with security, compliance, and scalability.
Document Versioning
Track every change with full version history and incremental indexing.
Role-Based Access
Admin, Member, and Viewer roles with granular permission controls.
Multi-Workspace
Isolated environments for teams, projects, and clients.
Audit Logs
Complete audit trail of all actions for compliance and security.
Evaluation Dashboard
RAGAS metrics, hallucination scoring, and quality monitoring.
Analytics
Usage metrics, latency tracking, cost analysis, and trends.
Monitoring
Real-time system health, alerts, and performance dashboards.
REST API
Full-featured API for programmatic document management and queries.
Webhooks
Event-driven integration with your existing infrastructure.
0+
Documents Indexed
0+
Queries Processed
0ms
Average Latency
0%
Hallucination Reduction
0+
Supported Models
Trusted by Engineering Teams
See how teams are using OmniRAG in production.
OmniRAG transformed our document search pipeline. We reduced query latency by 60% and eliminated hallucinations with the built-in detection system.
Sarah Chen
CTO, DataFlow Technologies
The multi-provider support is a game-changer. We switch between OpenAI and Claude based on task requirements without any code changes.
Marcus Rivera
Lead Engineer, FinAnalytica
Deploying on Vercel with zero Python dependencies saved us months of infrastructure work. The evaluation dashboard gives us confidence in production.
Priya Patel
VP Engineering, HealthStack
The hybrid search with reranking delivers remarkably accurate results. Our legal team now trusts AI-generated summaries with source citations.
James Wilson
Director of AI, LegalDocs Inc.
Frequently Asked Questions
Everything you need to know about OmniRAG.