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AI Engineering
Building RAG Systems That Don't Hallucinate on Your Own Data
May 18, 2026 · 6 min read
This is a placeholder article used to demonstrate the Insights layout. Replace with real, authored long-form content before publishing.
Retrieval quality matters more than model choice. A practical breakdown of what separates reliable RAG from brittle RAG.
A full article here would walk through the specific decisions, trade-offs, and lessons behind the topic above — grounded in how DigiRay’s engineering team actually approaches this kind of problem, with enough detail for a technical reader to act on.
Once real content is ready, this space becomes a genuine engineering note: what we tried, what didn’t work, and the reasoning that held up once the product met real users.