Building JOSIE: Advanced AI Workflow with Persistent Memory and Live Data Access

Build an uncensored AI assistant with persistent memory using n8n automation, vector databases, and privacy-focused web search

TL;DR: A advanced AI assistant using n8n workflow automation that combines JOSIEFIED-Qwen3:8b for intelligent responses, Qdrant vector database for persistent memory, and SearXNG for unlimited web search—all with complete data privacy.

Three-Component Architecture

Component 1: JOSIEFIED-Qwen3:8b – The Intelligent Core

JOSIEFIED-Qwen3:8b is built on Alibaba’s Qwen3 architecture with 8.19B parameters and a 40K context window. This uncensored language model offers better intelligence, extended context processing, tool integration, and complete local processing via Ollama with no external API dependencies. The JOSIEFIED model family includes variants from 4B to 14B parameters, with specialized versions for reasoning, healthcare, and other domains, all designed for privacy-preserving local deployment.

Component 2: Qdrant Vector Database – Persistent Memory

Qdrant transforms conversations into permanent knowledge. This open-source vector database lets you semantic search across all interactions with PDF processing, intelligent text chunking, high-quality embeddings using mxbai-embed-large:335m, and context retrieval with session-aware management. Vector quantization reduces RAM usage by up to 97% while maintaining sub-second search times.

Component 3: SearXNG – Unlimited Web Intelligence

SearXNG is a privacy-focused metasearch engine running locally on Docker providing unlimited queries with no rate limits, zero tracking, multi-engine aggregation from Google, Bing, and DuckDuckGo, plus clean JSON API access perfect for AI integration.

Real-World Applications

Personal Knowledge Management: Upload PDFs and query them conversationally. JOSIE remembers every discussion, creating a searchable knowledge base perfect for document analysis workflows.

Business Intelligence: Maintain context across long-term projects with customer support that remembers all interactions. Combine stored knowledge with live web data using business AI workflows.

Educational Companion: Track learning progress across topics while accessing academic papers and current web information through automated research pipelines.

Privacy and Security

All AI computations happen locally with no data leaving your network. GDPR-compliant with air-gapped setting it up options, complete audit trails, and full control over data retention using local set up strategies.

Technical Implementation

Visual workflow builder with Qdrant database using cosine similarity and HNSW indexing. 1024-dimensional vectors provide rich semantic representation with Ollama embeddings. The modular architecture scales efficiently with optimized storage, sub-second search times, and Kubernetes-ready setting it up for high availability.

Getting Started

Prerequisites: Docker, n8n instance, Ollama, Qdrant, and SearXNG.

Quick Setup: Deploy SearXNG using official Docker compose, install Qdrant with persistent storage, configure Ollama with JOSIEFIED-Qwen3:8b, import n8n workflow JSON, and configure service credentials.

The Future of AI Assistance

JOSIE represents a shift toward privacy-preserving AI that grows smarter with every interaction. By combining advanced language models, persistent memory, and unlimited web access under your complete control, it delivers business-grade features without vendor lock-in. Start with the n8n quickstart guide and explore AI workflow templates.

Related Resources

  • n8n Documentation – Complete guide to workflow automation
  • Qdrant Vector Database – Vector search documentation
  • Ollama Models – Local AI model library
  • SearXNG Setup – Privacy search engine guide
  • LangChain Integration – AI workflow building blocks

Tools & Platforms