I will build an advanced multimodal whatsapp rag ai agent in n8n


About this gig
Are you tired of basic, rigid chatbots that frustrate your customers?
I build Enterprise-Grade Multimodal AI Agents for WhatsApp using n8n, LangChain, and advanced Vector Databases (pgvector). My systems don't just "chat" they actively search your internal documents (RAG), process voice notes, analyze images, and seamlessly transfer complex issues to your human team.
What makes my AI architecture different:
- Multimodal Capabilities: The bot understands text, transcribes Voice Notes (Whisper API), and analyzes uploaded images/documents (Vision API).
- Advanced RAG (Retrieval-Augmented Generation): High-accuracy semantic search through your company's PDFs and manuals. The bot only gives factual answers based on YOUR data.
- Human-in-the-Loop: If the AI can't answer, or the user requests a manager, the system silently escalates the chat to your team in Slack or Telegram with full context.
- Self-Hosted & Secure: Built on n8n for maximum data privacy and control.
Stop losing leads to slow responses. Let's build a smart, autonomous support and sales engine for your business. Message me before ordering to discuss your specific workflows!
Get to know Valentine
Transforming Manual Workflows into AI Engines
- FromUkraine
- Member sinceMar 2026
- Avg. response time16 hours
Languages
English
FAQ
Question: Do I need to pay monthly fees for this bot?
Answer: You will need your own accounts for third-party services (like OpenAI, Groq, or WhatsApp Cloud API). n8n can be self-hosted for free or you can use their paid cloud version. I will help you set up the most cost-effective architecture!
Question: How does the "Human-in-the-Loop" feature work?
Answer: If the AI cannot answer a question or if a user specifically asks for a human manager, the bot will automatically pause and forward the chat history to your team in a Slack channel or Telegram group.
Question: Can the bot read our internal company PDFs and manuals?
Answer: Absolutely! The bot uses advanced RAG (Retrieval-Augmented Generation) technology and Vector Databases (like PostgreSQL/pgvector) to search your specific documents and provide highly accurate answers based ONLY on your data.

