Enterprise AI Solutions Architect

Shahvaiz Janjua

From C-suite strategy to demos I build — and take into production.

I work both sides of enterprise AI: scoping pilots and defining success criteria with the C-suite, then building the demos myself and taking them into production. Not vendor marketing, not toy demos — the real thing. The writing below is what I’ve learned doing it.

Or book a call →

Tap to speak

Featured writing

Pieces worth your time.

Read everything →

Illustration of two query lanes — instant reuse of approved SQL and a human-review path — converging on one database

Guide

Fast-or-Verify: Trustworthy NL-to-SQL with Human-in-the-Loop

Most NL-to-SQL demos are impressive — until you need real guarantees. A two-lane architecture that reuses human-approved SQL instantly and routes novel questions to review.

3 min read

End-to-end RAG architecture diagram: data ingestion via chunking, embedding and a vector store, feeding query response with semantic search and Generative AI

Guide

What Is Retrieval-Augmented Generation? RAG to Reality, Part 1

Part 1 of RAG to Reality: the use-cases that demand RAG, how ingestion (chunking, embedding, vector stores) and query flow actually work, and the enhancements that make RAG reliable.

10 min read