Most “AI for your business” work is a chat box over a prompt. This is the other kind: a retrieval system that reads your own material, cites what it used, and declines when your documents do not answer the question.
I know it works because I run one. Irshad AI Employee is a live multi-tenant product on this site - 946 Pakistani federal statutes and 2,552 Lahore High Court judgments, about 117,000 embedded chunks, answering on a website widget, on WhatsApp and in a web portal from a single engine. You can ask it something now without signing in.
The hard part is never the model. It is retrieval. Statute text defeats plain vector search because every passage reads alike - in my own corpus, the section answering “what is the punishment for theft” ranked 25th, behind a schedule of section numbers and an unrelated Ordinance, until I added a structural lookup that finds a provision by its printed heading. That is the sort of problem this work is really made of, and it is why a benchmark comes before a demo.
Stack I reach for: Django REST on Cloud Run, Postgres with pgvector, OpenAI embeddings and reasoning models, React or Astro on the front end. I will build in yours if you have one, and say plainly which I would choose and why.
