AI Developer Needed to Build Internal Knowledge Base Chatbot for Customer Support Team

We operate a software company with over 15,000 active customers and a growing support team. Our customer support agents currently spend a significant amount of time searching through documentation, training materials, PDFs, SOPs, and internal knowledge bases to answer customer questions. We are looking for an experienced AI Developer to build an intelligent internal AI assistant that can instantly retrieve information from our company knowledge base and help our support team resolve tickets faster. Project Goals The AI assistant should: * Answer questions based on our internal documents * Search across PDFs, SOPs, training guides, and help center articles * Provide source references for every answer * Help support agents draft responses to customers * Suggest troubleshooting steps * Learn from newly uploaded documents * Reduce average ticket resolution time Existing Stack Our current tools include: * HubSpot * Notion * Google Drive * Slack * Zendesk We are open to recommendations regarding the AI architecture. Preferred Skills We're looking for someone experienced with: * OpenAI API * Claude API * LangChain * RAG Applications * Vector Databases * AI Chatbots * Custom AI Agents * NLP * LLM Integration * Workflow Automation * API Integrations * Python Development * AI SaaS Development Nice To Have Experience with: * Flowise * Ollama * Open WebUI * Self-Hosted AI * Supabase * Docker * VPS Deployment Deliverables * AI chatbot application * Document ingestion pipeline * Knowledge base indexing system * User-friendly web interface * Authentication system * Deployment and documentation Application Requirements Please include: 1. Examples of RAG or AI chatbot projects you've built 2. Your preferred tech stack 3. How you would handle document indexing and retrieval 4. Estimated timeline and budget Budget: Open based on experience and proposed solution.