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AI Intelligence · RAG & Vector Search
Conversa AI — Self-Training Support Bot
An enterprise support chatbot that trains itself from a knowledge base with a full RAG pipeline, answers with grounded responses, and books rooms in conversation.
The AI core of my live Conversa AI platform (conversaai.net): it ingests a knowledge base, indexes it in a vector database, answers customer questions with grounded responses — and completes real room bookings inside the chat. Full platform case study under Development → Laravel. Live app: app.conversaai.net
Laravel 12Qdrant / PineconeOpenAILangChainNext.js 16Pusher
What it does
- End-to-end RAG — ingestion → chunking (800 / 120 overlap) → OpenAI embeddings → vector indexing, with versioned query pipelines promoted candidate → stable.
- Vector database — Qdrant (primary) or Pinecone behind one provider interface.
- Conversational room booking — natural-language availability detection, live resort-API checks and a guided date → payment → confirmation flow.
- Incremental auto-training via background jobs; new docs ingested through webhooks.
- Budget-aware LLM usage — per-company OpenAI budget manager with graceful AI fallback.
- Multi-company isolation with permission-scoped access.
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