Production SaaS Platform · Full-Stack · Founder & Sole Engineer
A domain-driven SaaS platform with five independently scalable system boundaries: scripture content delivery, RAG-backed AI study, real-time community interaction, async media processing, and infrastructure services — built and operated end-to-end.
Our Results
37K+
Verses Indexed
5
AI Models
5
Bounded Domains
3
Job Queues
How We Built It
RAG pipeline grounding AI responses in actual scripture rather than model memory
Hybrid Llama / OpenAI routing — local inference for cost, API fallback for quality at the edge
Non-blocking media processing — FFmpeg jobs enqueued via BullMQ, API never waits on transcoding
Cross-instance real-time consistency via Redis pub/sub behind WebSocket and WebRTC layers
Lessons Learned
Domain boundaries enforced at the service layer prevent coupling long before scale demands microservices.
RAG retrieval quality matters more than model size — better embeddings outperform a larger model on poor context.
Async queue design should be first-class, not bolted on; BullMQ worker isolation saved the request path repeatedly.