We write about the problems we hit, the paths we tried and what we learned. Engineering notes, not marketing copy.
A RAG system that looks flawless in a demo often breaks in production. Here are the five root causes we keep seeing across forty projects — and what we do about each.
Machine learning models do not fail loudly; they slowly become unfair. Here is the monitoring setup we build and how we choose thresholds that do not cry wolf.
Choosing between a database per tenant, a schema per tenant and row-level security is not a technology preference — it is a risk and cost decision. Notes from projects using all three.
Lab measurement loads a page once in a controlled environment. Real users do not behave that way. What we do when field data contradicts the lab score.
Whatever your idea, we have the technology and the team to make it real. Let’s start with a free one-hour discovery call.