Enterprise-grade Retrieval-Augmented Generation (RAG) system built with n8n that transforms how organizations access and utilize their private documents. Employees can instantly find accurate information from thousands of documents through natural language queries, eliminating hours of manual searching.

Organizations struggle with information silos where critical knowledge is locked away in PDFs, reports, contracts, and internal documents. Employees waste valuable time:

Searching through multiple folders and file systems

Reading lengthy documents to find specific information

Asking colleagues who might know where information exists

Recreating knowledge that already exists somewhere in the company

Missing important details buried in documentation

The cost? Hours of productivity lost daily, inconsistent information sharing, and delayed decision-making.

Developed a sophisticated RAG (Retrieval-Augmented Generation) system using n8n automation that creates an intelligent knowledge base from private company documents.

Secure document upload interface (PDF, DOCX, TXT, etc.)

Automatic text extraction and preprocessing

Document chunking for optimal retrieval

Metadata preservation (document name, date, author, department)

Documents converted into embeddings using Google Gemini Embedding models

Vector embeddings stored in Supabase Vector Database

Optimized indexing for fast similarity search

Maintains document context and relationships

Employees ask questions in natural language

Query converted to embeddings for semantic search

Relevant document chunks retrieved from Supabase

Context-aware responses generated using Google Gemini Chat

Answers include source citations for verification

n8n - Workflow automation and orchestration

Google Gemini Embedding Model - Converting text to vector embeddings

Google Gemini Chat - Generating accurate, contextual responses

Supabase Vector Database - Scalable vector storage with pgvector

Supabase Storage - Secure document file storage

Authentication & Security - Row-level security policies

✅ Semantic Search - Understands intent, not just keywords ✅ Multi-Document Intelligence - Synthesizes information across documents ✅ Source Citations - Every answer references original documents ✅ Privacy-First - All documents remain private in your Supabase instance ✅ Scalable - Handles thousands of documents efficiently ✅ Real-Time Updates - New documents immediately available for querying ✅ Department Filtering - Restrict searches to specific document sets ✅ Version Control - Track document updates and changes

⏱️ 90% reduction in time spent searching for information

📊 15+ hours saved per employee per week

🎯 95%+ accuracy in retrieving relevant information

🚀 Instant answers replacing hours of manual document review

Faster onboarding with instant access to company knowledge

Improved decision-making with comprehensive information retrieval

Reduced dependency on specific team members for information

Better compliance with quick access to policies and procedures

Enhanced collaboration across departments

HR Teams - Instantly pull information from employee handbooks, policies, and contracts

Sales Teams - Quick access to product specs, case studies, and pricing documents

Legal Departments - Search through contracts, agreements, and legal precedents

Customer Support - Find solutions from internal knowledge bases and troubleshooting guides

Engineering Teams - Access technical documentation, API specs, and architecture docs

End-to-end encryption for document storage

Role-based access control (RBAC)

Audit logs for all queries and document access

GDPR and SOC 2 compliant infrastructure

Data residency options available

Automated PII detection and redaction (optional)

Supabase database and storage configuration

n8n workflow development and testing

Security and authentication setup

Bulk document upload and processing

Vector embedding generation

Quality assurance and testing

User training and documentation

Integration with existing tools (Slack, Teams, etc.)

Monitoring and optimization

Query performance tuning

User feedback integration

Continuous accuracy improvements

✅ Fully configured n8n workflows (ingestion + query)

✅ Supabase database with vector search capability

✅ User-friendly query interface (web/Slack/Teams integration)

✅ Admin dashboard for document management

✅ Comprehensive documentation and training materials

✅ 30-day post-launch support and optimization

Typical ROI Timeline: 3-6 months

For a team of 50 employees saving 5 hours/week at $50/hour average:

Annual Savings: $650,000+

Intangible Benefits: Improved accuracy, faster decisions, better employee satisfaction

Unlike generic AI chatbots, this RAG system:

Works with YOUR proprietary documents

Provides verifiable, cited answers

Maintains complete data privacy

Scales with your organization

Integrates seamlessly into existing workflows

Ready to transform how your organization accesses knowledge? Let's build a custom RAG solution tailored to your specific needs and document types.