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.

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 OAuth
• Analytics 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.

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

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.