You will get Deploy Multi-Agent Systems with Vector Databases in n8n
Project details
Are you relying on fragile, UI-based automations that fail at scale? I engineer robust, fault-tolerant orchestration engines. I specialize in replacing linear integrations with autonomous, LLM-driven architectures deployed on self-hosted Docker environments.
My focus is strictly on backend systems engineering, API routing, and automation logic—ensuring your data is processed securely, accurately, and efficiently, free from the constraints of standard SaaS integration tools.
Core Capabilities:
Semantic Routing: Utilizing LangChain AI Agent nodes and Structured Output Parsers for dynamic payload routing.
RAG Infrastructure: Integrating vector databases (e.g., Supabase pgvector) with window buffer memory for context-aware agents.
Enterprise Security via MCP: Implementing local n8n-mcp servers, allowing LLMs to interact with databases securely without exposing REST APIs.
Payload Normalization: Custom JavaScript inside Code nodes for strict data validation and parsing before routing.
My focus is strictly on backend systems engineering, API routing, and automation logic—ensuring your data is processed securely, accurately, and efficiently, free from the constraints of standard SaaS integration tools.
Core Capabilities:
Semantic Routing: Utilizing LangChain AI Agent nodes and Structured Output Parsers for dynamic payload routing.
RAG Infrastructure: Integrating vector databases (e.g., Supabase pgvector) with window buffer memory for context-aware agents.
Enterprise Security via MCP: Implementing local n8n-mcp servers, allowing LLMs to interact with databases securely without exposing REST APIs.
Payload Normalization: Custom JavaScript inside Code nodes for strict data validation and parsing before routing.
AI Development Type
Recommendation SystemWhat's included
| Service Tiers |
Starter
$150
|
Standard
$400
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 4 days | 8 days | 14 days |
AI Model Integration | - | - | - |
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | - | - | - |
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
About Abdelrhmen
AI Automation Engineer | n8n, Make & OpenAI
Cairo, Egypt - 12:44 pm local time
My focus is simple: I design, build, and optimize no-code and AI-powered systems that pay for themselves through faster communication, smarter workflows, and measurable ROI.
📊 Proven Results from Recent Projects:
• +40% faster lead response time (Real Estate vertical).
• 25+ hours/month saved through n8n + HubSpot + Slack routing.
• +$10K added revenue in 60 days via automated follow-ups.
• 50% reduction in manual data entry errors.
⚙️ The Tech Stack I Master:
• Logic & Routing: n8n (Expert), Make, Zapier
• AI Models: OpenAI (GPT-4), Gemini, Anthropic
• Integrations: Webhooks, REST APIs, HubSpot, Slack, Airtable, G-Suite
Whether you need a smart customer support AI agent or a complex backend routing system, I build solutions that just work.
Let’s turn your processes into profit. Send me a message, and let's map out your next automation.
Steps for completing your project
After purchasing the project, send requirements so Abdelrhmen can start the project.
Delivery time starts when Abdelrhmen receives requirements from you.
Abdelrhmen works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: System Architecture & Scoping
You provide your API documentation, database schemas, and workflow requirements. I map out the technical blueprint, defining webhooks, data structures, and the required LLM prompt logic.
Step 2: Infrastructure & Logic Engineering
I build the core logic within n8n. This includes configuring the triggers, custom JavaScript code for data normalization, deploying the vector database connections, and setting up the LLM chains or AI Agents.