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Create RAG with Bult.ai

Nursultan

— 1 min read
Create RAG with Bult.ai

We just released a production ready RAG template project for Bult.ai.

If you want to deploy a serious Retrieval Augmented Generation (RAG) system, this is for you.

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Full step-by-step video tutorial is here: https://youtu.be/CkcVGtiSGDQ?si=Y1X1LP-Aw09g_zIp

Full tutorial text is here: https://docs.bult.ai/tutorials/tutorial-rag

What it includes:

  • Hybrid search combining BM25 and vector similarity
  • Cross encoder reranking for higher precision• Optional HyDE and multi query retrieval
  • Multi model support: OpenAI, Anthropic, Google, Ollama
  • OCR for scanned PDFs
  • JWT authentication and optional Google OAuthAnalytics dashboard with usage and latency tracking
  • Conversation export to Markdown, JSON, and PDF
  • Async background processing with job tracking

You upload documents. Ask questions. Get answers with inline citations and source scoring.

It deploys on Bult.ai using:

  • GitHub based app service
  • PostgreSQL
  • pgvector

No Kubernetes. No infrastructure gymnastics.

This template demonstrates how to run production grade AI workloads on a PaaS with full control over architecture.

If you're building AI products and need a strong RAG foundation, fork it and deploy in minutes.

Would love feedback from builders pushing RAG systems to real world scale.

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