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You will get RAG AI Agent in n8n: Smart Knowledge Base Chat with Source Retrieval
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Project details
We will build a RAG AI Agent in n8n that connects your knowledge sources and delivers accurate, context-aware answers instantly. Unlike generic chatbots, it retrieves relevant documents, cites sources, and adapts to your business knowledge, providing reliable, verifiable information.
Key benefits:
• Unified knowledge access: Combines Docs, PDFs, Notion, Confluence, websites, and databases.
• Contextual AI responses: Human-like, precise answers with references.
• Automated n8n workflows: Handles ingestion, indexing, retrieval, and feedback seamlessly.
• Continuous improvement: Learns from user feedback to refine answers.
• Traceable & credible: Each response includes source references.
This solution enables consistent, high-quality responses, reduces repetitive work, and scales as your knowledge grows, offering a smart, secure, and efficient system tailored to your organization.
Key benefits:
• Unified knowledge access: Combines Docs, PDFs, Notion, Confluence, websites, and databases.
• Contextual AI responses: Human-like, precise answers with references.
• Automated n8n workflows: Handles ingestion, indexing, retrieval, and feedback seamlessly.
• Continuous improvement: Learns from user feedback to refine answers.
• Traceable & credible: Each response includes source references.
This solution enables consistent, high-quality responses, reduces repetitive work, and scales as your knowledge grows, offering a smart, secure, and efficient system tailored to your organization.
AI Algorithms
Large Language Model, Long Short-Term Memory Network, Transformer ModelAI Applications
AI ChatbotAI Development Language
PythonAI Models
ChatGPT, DALL-E, GPT-3, GPT-4, GPT-Neo, LLaMAWhat's included $300
These options are included with the project scope.
$300
- Delivery Time 2 days
- Number of Revisions 2
- AI Model Integration
- Natural Language Processing
- NLP Tokenization
- Prompt Engineering
Frequently asked questions
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LS
Leo S.
Jun 23, 2026
AI lead generation system
Great work!
PG
Pierluigi G.
Jan 7, 2026
Automation Expert with Experience with Bonsai
Aman was a pleasure to work with, he went above and beyond every request. Highly reccomended!
AT
Anthony T.
Dec 12, 2025
Task
About Aman
AI Systems Engineer for Agencies | n8n, AI Agents, Make, Supabase
100%
Job Success
Lahore, Pakistan - 10:10 am local time
My focus is on delivering workflows that are clean, well-documented, and built to perform long-term — not just functional on delivery day.
What I can build for you:
⚡ End-to-end marketing & lead generation automation using Make. com, n8n, and Zapier
⚡ CRM workflow automation with HubSpot, GoHighLevel, and Airtable
⚡ AI-powered workflows using OpenAI and ChatGPT Assistants API
⚡ Custom REST API & Webhook integrations between any tools or platforms
⚡ Automated reporting, data pipelines, and real-time notifications
⚡ Large-scale content and website generation using Make. com + AI
⚡ Migration of existing automations between Zapier, Make. com, and n8n
⚡ Troubleshooting and optimizing broken or inefficient workflows
My approach:
🚀 Understand first — I begin with a thorough analysis of your current workflows to identify where automation will deliver the most impact
🚀 Build clean — Every solution is structured, documented, and built to be maintainable by your team long after delivery
🚀 Support after delivery — I remain available post-launch for adjustments, improvements, and ongoing maintenance
With a background in Data Science, I bring both technical depth and business thinking to every engagement.
100% Job Success Score. Let's discuss how automation can improve your operations — feel free to reach out.
Steps for completing your project
After purchasing the project, send requirements so Aman can start the project.
Delivery time starts when Aman receives requirements from you.
Aman works on your project following the steps below.
Revisions may occur after the delivery date.
Knowledge Ingestion & Indexing
Collect and process documents from all sources, split into chunks, create embeddings, and store in the chosen vector database.
Workflow & Retrieval Setup
We will build n8n workflows for document retrieval, reranking, and generating context-aware prompts for the LLM.