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AI Knowledge Base (RAG) Chatbot
Overview
Developed a Retrieval-Augmented Generation (RAG) chatbot that indexes documents uploaded to Google Drive, stores them in a vector database, and answers user questions using the company's own knowledge.
Business Value
- Gives employees instant access to company information
- Reduces time spent searching through documents
- Improves the accuracy of AI responses
- Makes internal knowledge easier to access
Technologies
n8n • Google Drive • Pinecone • Google Gemini Embeddings • OpenRouter • AI Agent
The network for creativity
Join 1.25M professional creatives like you
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Creatives on Contra have earned over $150M and we are just getting started
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I’m currently building a RAG system for an e-commerce company, basically giving an AI assistant access to the company’s own knowledge and product information so it can give useful, context-aware responses instead of just generating random answers.
The interesting part isn’t just connecting an LLM.
It’s making sure the AI can:
→ Find the right information
→ Understand the user’s question
→ Retrieve relevant context
→ Give an accurate response
→ Actually be useful in a real business workflow
Still working on it, but I’m excited about where it’s going.
This is the kind of AI automation I enjoy building, systems that solve actual business problems, not just AI demos.
Building something similar? Let’s talk.
One thing that will save you a lot of time: build a small evaluation set early — 50–100 real questions with the document or product that should be retrieved for each. Before tuning prompts, measure retrieval quality (does the right doc surface in the top 3?) with it. Chunk size...
People don’t like to wait for your customer support system.
It shows that you don’t care enough for your users.
Introducing Assistia, a template for AI customer service automation platforms.
Designed specifically for SaaS companies.
It’ll reduce response times and cut support costs by up to 70%.
With its visual storytelling and social proof sections, strategic CTAs, and mobile-first design,
You can launch your website fast.
Check the comments for the links.
This is my AI Customer Support and Lead Generation Agent, built with n8n.
The workflow starts when a customer sends a message. The AI Agent understands the customer's request and responds automatically.
It also uses conversation memory to maintain context during the conversation.
When a customer wants to place an order, the agent collects important details such as their name, phone number, email, service, quantity, and requirements.
Finally, the customer's information is automatically saved into Google Sheets as a new lead.
This automation helps businesses handle customer inquiries and organize leads without manual work.
Agents are amazing. Building & using them is a genuine wise career choice in my opinion.
