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AI Company Knowledge System from Scratch

MakeTheJump AI 313 1 month ago
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What if you could analyze real customer feedback or investment commentary from your emails, podcast notes, and transcripts—automatically? Learn the secrets to AI implementations that actually work: https://www.makethejump.ai/ai-implementation-handbook Want someone to build an AI implementation for you? Check out my team here: https://www.navispect.com/ In this video, we walk through how to build a complete AI-powered system that captures incoming emails, stores the important data in a vector database, and gives you a chatbot interface to query insights—whether you want to summarize customer complaints, track product feedback trends, or just search across your knowledge base. You'll learn: How to filter useful content from emails using AI classification How to store and search that content using vector embeddings How to build a chatbot agent that understands your data and gives you instant answers This is like having a private AI research assistant that knows your business inside and out. Tools Used in This Tutorial: n8n – https://n8n.io OpenAI (GPT-4o Mini, Embeddings) – https://platform.openai.com Pinecone Vector Database – https://www.pinecone.io Gmail Integration via n8n – https://n8n.io/integrations/google Hugging Face (alternative free embedding models) – https://huggingface.co Helpful Links: Pinecone + OpenAI Quickstart – https://docs.pinecone.io/docs/quickstart Gmail integration setup in n8n – https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.gmail/ Hugging Face Text Embedding Models – https://huggingface.co/models?pipeline_tag=feature-extraction&sort=downloads Using Text Classifier node in n8n – https://docs.n8n.io/nodes/n8n-nodes-base.textClassifier/ AI Agent node documentation in n8n – https://docs.n8n.io/nodes/n8n-nodes-base.aiAgent/ Chapters: 00:00 Introduction to AI-Powered Knowledge Systems 00:21 Building the Chat Bot 00:39 Curating Data for Better Results 00:52 Creating the Intake Process 01:08 Accessing and Filtering Emails 02:09 Classifying Product Feedback 03:36 Storing Data in Vector Databases 03:59 Understanding Vector Databases 05:18 Configuring Pine Cone Vector Store 06:20 Inserting Emails into the Database 08:57 Testing the Workflow 12:03 Creating the Chat Bot Interface 15:04 Finalizing the Chat Bot 17:27 Conclusion and Next Steps

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