Luwi Semantic Bridge

ContextIntelligence

Transform scattered enterprise knowledge into an intelligent memory layer. AI-powered semantic search, retrieval-augmented generation, and n8n workflow automation — all open source.

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What is SemanticBridge?

A Context Engine that turns PDFs, web pages, databases, and internal documents into a single AI-accessible knowledge layer. Hybrid semantic search finds the right context in milliseconds; RAG generates grounded answers; n8n workflows automate everything around it.

Key Features

Semantic RAG

Natural-language Q&A grounded in your documents. GPT-4 answers with citations, multilingual context awareness, and full source transparency.

Hybrid Search

Three-layer strategy: pgvector similarity, PostgreSQL full-text, and fuzzy trigram matching. Sub-50ms response with 95%+ accuracy.

Document Processing

PDF, DOCX, HTML, JSON, CSV — with OCR for scanned files. Smart chunking, metadata extraction, automatic classification, embeddings.

n8n Integration

15+ custom n8n nodes for automation pipelines, webhooks for real-time sync, scheduled jobs, and native workflow orchestration.

Knowledge Graph

Auto-detect relationships between documents, entities, and concepts. 3D visualization, temporal context, domain-specific learning.

Multi-tenant

Workspace isolation, role-based access control, API key management, usage quotas, and complete audit logging for enterprise scale.

Built for real workflows

Enterprise Knowledge

A decade of documents scattered across departments unified into a searchable semantic database. Employees ask questions in plain language; the system surfaces relevant docs with citations.

70% faster info access
Legal Tech & Compliance

Hundreds of regulations, court rulings, and articles auto-indexed. Citation networks reveal precedents; semantic search finds applicable cases instantly.

80% search time reduction
Healthcare

Medical protocols, research papers, and patient cases indexed semantically. Symptom-based search, automatic case similarity, AI-summarized treatment protocols.

Evidence-based decisions
Education & Media

Course materials and content archives become an AI tutor. Personalized learning paths, 24/7 student support, automatic tagging, content recommendations.

50% content velocity

How it works

01

Ingest

Upload documents or connect data sources. Auto-processing extracts text, metadata, and structure.

02

Embed

Smart chunking and vector embeddings generated. Multi-layer indexing for hybrid search across content.

03

Query

Natural language questions hit the hybrid search engine. Relevant chunks retrieved in <50ms.

04

Augment

GPT-4 generates grounded answers with source citations. Workflows trigger via n8n for automation.

Why SemanticBridge

Open Source (MIT)

No vendor lock-in. Self-host or deploy to cloud. Community-driven development.

Enterprise-Ready

Multi-tenant by design, horizontal scaling, high availability, comprehensive monitoring.

Easy Integration

REST API, WebSocket support, n8n workflows, webhook events — fits any architecture.

Cost-Effective

No license fees. Run on your own infrastructure. Optimized caching reduces API costs.

Tech Stack
Node.js 18+PostgreSQL 15 + pgvectorRedis 7+Next.js 15Dockern8n

Frequently asked questions

SemanticBridge is not just a vector store — it is a full context engine. It combines pgvector + full-text + fuzzy search in one query, processes documents end-to-end (chunking, metadata, OCR), and ships with n8n workflow nodes for automation. You own all of it. No SaaS bills, no vendor lock-in.

Bring your enterprise knowledge to life

Open source, enterprise-ready, self-hostable. Start in 5 minutes with Docker.